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\n  \n 2023\n \n \n (7)\n \n \n
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\n \n\n \n \n \n \n \n Motion Prediction in Fibre-Reinforced Polymer Preforming.\n \n \n \n\n\n \n Max Van Gemmeren.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, April 2023.\n \n\n\n\n
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@thesis{gemmeren2023,\n  author      = {Van Gemmeren, Max},\n  title       = {Motion Prediction in Fibre-Reinforced Polymer Preforming},\n  year        = {2023},\n  month       = apr,\n  school      = {{RWTH Aachen University}},\n  type        = {bathesis},\n  advisor     = {Behery, Mohamed},\n  keywords    = {Machine Learning, Textile Manufacturing}\n}\n\n
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\n \n\n \n \n \n \n \n Knowledge Graphs as a Dynamic Semantic Interface to the Internet of Production.\n \n \n \n\n\n \n Mathis Fütterer.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, April 2023.\n \n\n\n\n
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@thesis{fuetterer2023,\n  author      = {Mathis Fütterer},\n  title       = {Knowledge Graphs as a Dynamic Semantic Interface to the Internet of Production},\n  year        = {2023},\n  month       = apr,\n  school      = {{RWTH Aachen University}},\n  type        = {bathesis},\n  advisor     = {Behery, Mohamed},\n  keywords    = {Knowledge Graph, Decision Support System}\n}\n\n
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\n \n\n \n \n \n \n \n Human Action Nodes for Behavior Trees.\n \n \n \n\n\n \n Jonas Deutsch.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, April 2023.\n \n\n\n\n
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@thesis{deutsch2023,\n  author      = {Jonas Deutsch},\n  title       = {Human Action Nodes for Behavior Trees},\n  year        = {2023},\n  month       = apr,\n  school      = {{RWTH Aachen University}},\n  type        = {bathesis},\n  advisor     = {Behery, Mohamed},\n  keywords    = {Behavior Trees, Agent, Behavior Modeling, Human-Robot Interaction}\n}\n\n
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\n \n\n \n \n \n \n \n McFAT RL: Multi-Agent Collaboration for Assembly Tasks using Reinforcement Learning.\n \n \n \n\n\n \n Muhammad Waqas.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, March 2023.\n \n\n\n\n
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@thesis{waqas2023,\n  author      = {Muhammad Waqas},\n  title       = {McFAT RL: Multi-Agent Collaboration for Assembly Tasks using Reinforcement Learning},\n  year        = {2023},\n  month       = mar,\n  school      = {{RWTH Aachen University}},\n  type        = {mathesis},\n  advisor     = {Behery, Mohamed},\n  keywords    = {Reinforcement Learning, Multi-agent systems}\n}\n\n
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\n \n\n \n \n \n \n \n \n Development of an Analytics Infrastructure for Milling Processes.\n \n \n \n \n\n\n \n Muhammad Mehmood Ahmed.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, March 2023.\n \n\n\n\n
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@thesis{Ahmed2023,\n  author      = {Muhammad Mehmood Ahmed},\n  title       = {Development of an Analytics Infrastructure for Milling Processes},\n  url = {https://kbsg.rwth-aachen.de/theses/ahmed2023.pdf},\n  year        = {2023},\n  month       = mar,\n  school      = {{RWTH Aachen University}},\n  type        = {bathesis},\n  advisor     = {Viehmann, Tarik and Ochel, Janis},\n  keywords    = {clustering, time series, milling}\n}\n
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\n \n\n \n \n \n \n \n \n Using Reinforcement Learning as Goal Selector in Goal Reasoning.\n \n \n \n \n\n\n \n Sonja Ginter.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, April 2023.\n \n\n\n\n
\n\n\n\n \n \n \"UsingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 42 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@thesis{Ginter2023,\n  author      = {Sonja Ginter},\n  title       = {Using Reinforcement Learning as Goal Selector in Goal Reasoning},\n  url = {https://kbsg.rwth-aachen.de/theses/ginter2023.pdf},\n  year        = {2023},\n  month       = apr,\n  school      = {{RWTH Aachen University}},\n  type        = {mathesis},\n  advisor     = {Viehmann, Tarik and Hofmann, Till},\n  keywords    = {reinforcement learning, RCLL, goal reasoning}\n}\n\n
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\n \n\n \n \n \n \n \n \n A ROS 2 based Markerless MPS Pose Estimation for the RoboCup Logistics League.\n \n \n \n \n\n\n \n Daniel Honies.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, August 2023.\n \n\n\n\n
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@thesis{Honies2023,\n  author      = {Daniel Honies},\n  title       = {A ROS 2 based Markerless MPS Pose\nEstimation for the RoboCup Logistics League},\n  url = {https://kbsg.rwth-aachen.de/theses/honies2023.pdf},\n  year        = {2023},\n  month       = aug,\n  school      = {{RWTH Aachen University}},\n  type        = {bathesis},\n  advisor     = {Viehmann},\n  keywords    = {machine learning, RCLL, object detection, robotics}\n}\n
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\n \n\n \n \n \n \n \n Computer Vision for safety in Collaborative Assembly.\n \n \n \n\n\n \n David Kötter.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, September 2022.\n \n\n\n\n
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@thesis{koetter2022,\n  author      = {K{\\"o}tter, David},\n  title       = {Computer Vision for safety in Collaborative Assembly},\n  year        = {2022},\n  month       = sep,\n  school      = {{RWTH Aachen University}},\n  type        = {mathesis},\n  advisor     = {Behery, Mohamed},\n  keywords    = {Robotic Assembly, Human-Robot Collaboration, Behavior Trees}\n}\n\n
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\n \n\n \n \n \n \n \n Dynamics Moldeling of Industrial Robots Using Transformer Networks.\n \n \n \n\n\n \n Mahmoud Emara.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, September 2022.\n \n\n\n\n
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@thesis{emara2022,\n  author      = {Mahmoud Emara},\n  title       = {Dynamics Moldeling of Industrial Robots Using Transformer Networks},\n  year        = {2022},\n  month       = sep,\n  school      = {{RWTH Aachen University}},\n  type        = {mathesis},\n  advisor     = {Behery, Mohamed},\n  keywords    = {Supervised Learning, Dynamics modeling, Machening, Transformers}\n}\n\n\n
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\n \n\n \n \n \n \n \n Verifying Belief Program by Symbolic Dynamic Programming.\n \n \n \n\n\n \n Huang Qinfei.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, Aachen, 2022.\n \n\n\n\n
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@thesis{ qinfei_msthesis,\n  title    = {Verifying Belief Program by\nSymbolic Dynamic Programming},\n  author   = {Qinfei, Huang},\n  year     = {2022},\n  school   = {RWTH Aachen University},\n  type     = {mathesis},\n  address  = {Aachen},\n  advisor     = {Daxin, Liu},\n  keywords = {program verification, epistemic program, probabilistic program},\n  abstract    = {\nThe action programming language Golog is a powerful tool for expressing\nhigh-level agent behaviors. One advantage of programming in Golog is that its logical foundation, the situation calculus, makes formal analyse of programs’ behaviour\npossible. As a probabilistic extension of the Golog programming language family,\nBelle and Levesque  proposed a framework called belief programs where every\naction and sensing could be noisy and test refers to the agent’s subjective belief. These\ncharacteristics, among others, make belief programs rather suitable for robot control\nin a partial-observable uncertain environment.\nBefore deployment, it is desirable to verify programs meet certain properties as\ndesired. To fulfil the task, Liu and Lakemeyer reconsider the proposal of belief\nprograms by Belle and Levesque  based on a probabilistic modal logic of belief\nand actions, i.e. the logic DSp. Among other things, their proposal allows expressing\nprogram properties in a variant of PCTL logic. Liu and Lakemeyer [Liuar] also show\nthat the verification problem is closely related to model-checking infinite horizon partial\nobservable Markov decision process (POMDP), therefore is undecidable. They show\nthat the problem is strongly undecidable even under very restrictive settings, nevertheless, they prove that for bounded temporal properties, the verification problem could\nbe decidable, assuming the underlying logic is decidable.\nDespite many theoretical results they achieved, a general algorithm that actually\nconducts the verification is missing. In this thesis, we propose an algorithm based\non symbolic dynamic programming to verify belief programs. Symbolic dynamic programming (SDP) is a generalization of the dynamic programming technique for solving\nMarkov decision processes (MDPs) that exploits the symbolic structure in the solution\nof relational and first-order logical MDPs through a lifted version of dynamic programming. Such technique suits it well in verifying belief programs.\n}\n}\n\n\n
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\n The action programming language Golog is a powerful tool for expressing high-level agent behaviors. One advantage of programming in Golog is that its logical foundation, the situation calculus, makes formal analyse of programs’ behaviour possible. As a probabilistic extension of the Golog programming language family, Belle and Levesque proposed a framework called belief programs where every action and sensing could be noisy and test refers to the agent’s subjective belief. These characteristics, among others, make belief programs rather suitable for robot control in a partial-observable uncertain environment. Before deployment, it is desirable to verify programs meet certain properties as desired. To fulfil the task, Liu and Lakemeyer reconsider the proposal of belief programs by Belle and Levesque based on a probabilistic modal logic of belief and actions, i.e. the logic DSp. Among other things, their proposal allows expressing program properties in a variant of PCTL logic. Liu and Lakemeyer [Liuar] also show that the verification problem is closely related to model-checking infinite horizon partial observable Markov decision process (POMDP), therefore is undecidable. They show that the problem is strongly undecidable even under very restrictive settings, nevertheless, they prove that for bounded temporal properties, the verification problem could be decidable, assuming the underlying logic is decidable. Despite many theoretical results they achieved, a general algorithm that actually conducts the verification is missing. In this thesis, we propose an algorithm based on symbolic dynamic programming to verify belief programs. Symbolic dynamic programming (SDP) is a generalization of the dynamic programming technique for solving Markov decision processes (MDPs) that exploits the symbolic structure in the solution of relational and first-order logical MDPs through a lifted version of dynamic programming. Such technique suits it well in verifying belief programs. \n
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\n \n\n \n \n \n \n \n \n Multi-Agent System for Production Processes in the Automotive Industry.\n \n \n \n \n\n\n \n Maximilian Kerpen.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, April 2022.\n \n\n\n\n
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@thesis{Kerpen2022,\n  author      = {Maximilian Kerpen},\n  title       = {Multi-Agent System for Production Processes in the Automotive Industry},\n  url = {https://kbsg.rwth-aachen.de/theses/kerpen2022.pdf},\n  year        = {2022},\n  month       = apr,\n  school      = {{RWTH Aachen University}},\n  type        = {bathesis},\n  advisor     = {Liebenberg, Martin and Viehmann, Tarik},\n  keywords    = {MAS, Agent, Ontologies, Distributed Systems, WWL}\n}\n\n
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\n \n\n \n \n \n \n \n \n Utilizing a PDDL Goal Model for Goal Reasoning with the CLIPS Executive.\n \n \n \n \n\n\n \n Patrick Lusts.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, April 2022.\n \n\n\n\n
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@thesis{Lusts2022,\n  author      = {Patrick Lusts},\n  title       = {Utilizing a PDDL Goal Model for Goal Reasoning with the CLIPS Executive},\n  url = {https://kbsg.rwth-aachen.de/theses/lusts2022.pdf},\n  year        = {2022},\n  month       = apr,\n  school      = {{RWTH Aachen University}},\n  type        = {bathesis},\n  advisor     = {Viehmann, Tarik},\n  keywords    = {Goal Reasoning, PDDL, Planning, Clips Executive}\n}\n\n
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\n \n\n \n \n \n \n \n \n Whole-Body Manipulation on Mobile Robots Using Parallel Position-Based Visual Servoing.\n \n \n \n \n\n\n \n Matteo Tschesche.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, May 2022.\n \n\n\n\n
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@thesis{Tschesche2022,\n  author      = {Matteo Tschesche},\n  title       = {Whole-Body Manipulation on Mobile Robots Using Parallel Position-Based Visual Servoing},\n  url         = {https://kbsg.rwth-aachen.de/theses/tschesche2022.pdf},\n  year        = {2022},\n  month       = may,\n  school      = {{RWTH Aachen University}},\n  type        = {mathesis},\n  advisor     = {Hofmann, Till},\n  keywords    = {visual servoing, robotics, manipulation, RCLL}\n}\n\n
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\n \n\n \n \n \n \n \n An Approach to Instance Segmentation and Pose Estimation for Automated Dismantling of Lithium-Ion Batteries for High-Quality Recycling.\n \n \n \n\n\n \n Anna-Maria Meer.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, July 2022.\n \n\n\n\n
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@thesis{Meer2022,\n  author  = {Anna-Maria Meer},\n  title   = {An Approach to Instance Segmentation and Pose Estimation for Automated Dismantling of Lithium-Ion Batteries for High-Quality Recycling},\n  year    = {2022},\n  month   = jul,\n  school  = {{RWTH Aachen University}},\n  type    = {mathesis},\n  advisor = {Christina Ionescu and Till Hofmann and Alexander von Rohr}\n}\n\n
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\n \n\n \n \n \n \n \n \n Transfer Reinforcement Learning in a Distributed Laser-Based Manufactoring System.\n \n \n \n \n\n\n \n Irina Sutyrina.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, July 2022.\n \n\n\n\n
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@thesis{Sutyrina2022,\n  author      = {Irina Sutyrina},\n  title       = {Transfer Reinforcement Learning in a Distributed Laser-Based Manufactoring System},\n  url = {https://kbsg.rwth-aachen.de/theses/sutyrina2022.pdf},\n  year        = {2022},\n  month       = jul,\n  school      = {{RWTH Aachen University}},\n  type        = {mathesis},\n  advisor     = {Viehmann, Tarik and Kröger, Moritz},\n  keywords    = {reinforcement learning, transfer learning, laser-based manufactoring}\n}\n\n
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\n \n\n \n \n \n \n \n \n A CLIPS-Based CBR Framework for Pass Schedule Recommendations in Open-Die Forging.\n \n \n \n \n\n\n \n Sarah Soomro.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, November 2022.\n \n\n\n\n
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@thesis{Soomro2022,\n  author      = {Sarah Soomro},\n  title       = {A CLIPS-Based CBR Framework for Pass Schedule Recommendations in Open-Die Forging},\n  url = {https://kbsg.rwth-aachen.de/theses/soomro2022.pdf},\n  year        = {2022},\n  month       = nov,\n  school      = {{RWTH Aachen University}},\n  type        = {bathesis},\n  advisor     = {Viehmann, Tarik},\n  keywords    = {case-based reasoning, pass schedule recommendations, open-die forging}\n}\n\n
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\n \n\n \n \n \n \n \n Reasoning about Belief by Progression.\n \n \n \n\n\n \n Feng Qihui.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, Aachen, 2021.\n \n\n\n\n
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@thesis{ qihui_msthesis,\n  title    = {Reasoning about Belief by Progression},\n  author   = {Qihui, Feng},\n  year     = {2021},\n  school   = {RWTH Aachen University},\n  type     = {mathesis},\n  advisor     = {Daxin, Liu},\n  address  = {Aachen},\n  keywords = {knowledge representation, progression of belief},\n  abstract={\nBased on weighted possible worlds semantics, Belle and Lakemeyer recently proposed the logic DS, a probabilistic extension of a modal variant of the situation\ncalculus with a model of belief. The logic has many desirable properties like full\nintrospection and it is able to precisely capture the beliefs of a probabilistic knowledge base in terms of the notion of only-believing. While intuitively appealing, it\nis unclear how to plan with such logic. The fundamental problem behind is the lack\nof projection reasoning mechanisms.\nProjection reasoning, in general, is to decide what holds after actions. Two\nmain solutions to projection exist: regression and progression. Roughly, regression\nreduces a query about the future to a query about the initial state. Progression,\non the other hand, changes the initial state according to the effects of actions and\nthen checks whether the formula holds in the updated state. In this thesis we\nstudy projection by progression in the logic DS. It is known the progression of a\ncategorical knowledge base w.r.t. a noise-free action corresponds to what is only known after that action. We show how to progress a type of probabilistic knowledge\nbase by the notion of only-believing after actions.\n} \n}\n\n
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\n Based on weighted possible worlds semantics, Belle and Lakemeyer recently proposed the logic DS, a probabilistic extension of a modal variant of the situation calculus with a model of belief. The logic has many desirable properties like full introspection and it is able to precisely capture the beliefs of a probabilistic knowledge base in terms of the notion of only-believing. While intuitively appealing, it is unclear how to plan with such logic. The fundamental problem behind is the lack of projection reasoning mechanisms. Projection reasoning, in general, is to decide what holds after actions. Two main solutions to projection exist: regression and progression. Roughly, regression reduces a query about the future to a query about the initial state. Progression, on the other hand, changes the initial state according to the effects of actions and then checks whether the formula holds in the updated state. In this thesis we study projection by progression in the logic DS. It is known the progression of a categorical knowledge base w.r.t. a noise-free action corresponds to what is only known after that action. We show how to progress a type of probabilistic knowledge base by the notion of only-believing after actions. \n
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\n \n\n \n \n \n \n \n \n Goal Reasoning with the CLIPS Executive in ROS2.\n \n \n \n \n\n\n \n Ivaylo Doychev.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, October 2021.\n \n\n\n\n
\n\n\n\n \n \n \"GoalPaper\n  \n \n \n \"Goal code\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 9 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@thesis{Doychev2021,\n  author = {Ivaylo Doychev},\n  title = {Goal Reasoning with the CLIPS Executive in ROS2},\n  year = {2021},\n  month = oct,\n  school = {{RWTH Aachen University}},\n  type = {bathesis},\n  advisor = {Viehmann, Tarik and Hofmann, Till},\n  url = {https://kbsg.rwth-aachen.de/theses/doychev2021.pdf},\n  url_Code = {https://github.com/fawkesrobotics/ros2-clips-executive}\n}\n\n
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\n \n\n \n \n \n \n \n Performance Prediction in Object-Centric Event Logs.\n \n \n \n\n\n \n Timo Rohrer.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, March 2021.\n \n\n\n\n
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@thesis{Rohrer2021,\n  author      = {Timo Rohrer},\n  title       = {Performance Prediction in Object-Centric Event Logs},\n  year        = {2021},\n  month       = mar,\n  school      = {{RWTH Aachen University}},\n  type        = {bathesis},\n  advisor     = {Behery, Mohamed},\n  keywords    = {process mining}\n}\n\n\n
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\n \n\n \n \n \n \n \n Dynamic Sequence Nodes for Increased Behavior Tree Robustness.\n \n \n \n\n\n \n Biliana Naumova.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, November 2021.\n \n\n\n\n
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@thesis{Naumova2021,\n  author      = {Biliana Naumova},\n  title       = {Dynamic Sequence Nodes for Increased Behavior Tree Robustness},\n  year        = {2021},\n  month       = nov,\n  school      = {{RWTH Aachen University}},\n  type        = {bathesis},\n  advisor     = {Behery, Mohamed},\n  keywords    = {Behavior Trees, Agent, Behavior Modeling, Action Execution}\n}\n\n
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\n  \n 2020\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n Learning a Behavior Tree Library from Observations.\n \n \n \n\n\n \n Leo Krömker.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, June 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@thesis{Kroemker2020,\n  author      = {Leo Krömker},\n  title       = {Learning a Behavior Tree Library from Observations},\n  year        = {2020},\n  month       = jun,\n  school      = {{RWTH Aachen University}},\n  type        = {mathesis},\n  advisor     = {Behery, Mohamed},\n  abstract    = { Due to the rise of artificial intelligence in the context of the ”fourth industrial revolution”, the interest in learning systems has grown drastically. Blackbox\nmodels such as neural networks, however, are not transparent and cannot\nbe maintained or adjusted by humans. Behavior trees provide a solution for\nthis problem as they are expressive, structured, and human-readable. In this\nthesis a method is designed to learn common behaviors from observations.\nFor that, common behavior patterns are extracted and a semantic description\nof these patterns is derived. The work will be evaluated using StarCraft II\nas a test bed by learning the behaviors of professional players from publicly\navailable replay datasets.},\n  keywords    = {Production Scheduling, Combinatorial Optimization, Machine Learning, Deep Reinforcement Learning}\n}\n\n
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\n Due to the rise of artificial intelligence in the context of the ”fourth industrial revolution”, the interest in learning systems has grown drastically. Blackbox models such as neural networks, however, are not transparent and cannot be maintained or adjusted by humans. Behavior trees provide a solution for this problem as they are expressive, structured, and human-readable. In this thesis a method is designed to learn common behaviors from observations. For that, common behavior patterns are extracted and a semantic description of these patterns is derived. The work will be evaluated using StarCraft II as a test bed by learning the behaviors of professional players from publicly available replay datasets.\n
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\n \n\n \n \n \n \n \n \n Centralized Goal Reasoning And Scheduling Using Mixed Integer Programming for Logistics Robots.\n \n \n \n \n\n\n \n Mostafa Gomaa.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, August 2020.\n \n\n\n\n
\n\n\n\n \n \n \"CentralizedPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@thesis{Gomaa2020,\n  author = {Mostafa Gomaa},\n  title = {Centralized Goal Reasoning And Scheduling Using Mixed Integer Programming for Logistics Robots},\n  year = {2020},\n  month = aug,\n  school = {{RWTH Aachen University}},\n  type = {mathesis},\n  advisor = {Hofmann, Till},\n  url = {https://kbsg.rwth-aachen.de/~hofmann/theses/gomaa.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n \n Sharing Promises and Requests in Multi-Agent Goal Reasoning for Logistics Robots.\n \n \n \n \n\n\n \n Daniel Swoboda.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, September 2020.\n \n\n\n\n
\n\n\n\n \n \n \"SharingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 8 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@thesis{Swoboda2020,\n  author = {Daniel Swoboda},\n  title = {Sharing Promises and Requests in Multi-Agent Goal Reasoning for Logistics Robots},\n  year = {2020},\n  month = sep,\n  school = {{RWTH Aachen University}},\n  type = {bathesis},\n  advisor = {Hofmann, Till},\n  url = {https://kbsg.rwth-aachen.de/~hofmann/theses/swoboda.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n \n Multi-agent system for supply chain management in the textile industry.\n \n \n \n \n\n\n \n Nikola Balog.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, October 2020.\n \n\n\n\n
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@thesis{Balog2020,\n  author      = {Nikola Balog},\n  title       = {Multi-agent system for supply chain management in the textile industry},\n  url = {https://kbsg.rwth-aachen.de/theses/balog2020.pdf},\n  year        = {2020},\n  month       = oct,\n  school      = {{RWTH Aachen University}},\n  type        = {bathesis},\n  advisor     = {Liebenberg, Martin},\n  keywords    = {MAS, Agent, Data Provenance, WWL}\n}\n\n
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\n  \n 2019\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n \n Using Platform Models for a Guided Explanatory Diagnosis Generation for Mobile Robots.\n \n \n \n \n\n\n \n Daniel Habering.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, August 2019.\n \n\n\n\n
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@thesis{Habering2019,\n  author = {Habering, Daniel},\n  title = {Using Platform Models for a Guided Explanatory Diagnosis Generation for Mobile Robots},\n  year = {2019},\n  month = aug,\n  school = {{RWTH Aachen University}},\n  type = {mathesis},\n  advisor = {Hofmann, Till},\n  url = {https://kbsg.rwth-aachen.de/~hofmann/theses/habering.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n \n Transforming Robotic Plans with Timed Automata to Solve Temporal Platform Constraints.\n \n \n \n \n\n\n \n Tarik Viehmann.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, December 2019.\n \n\n\n\n
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@thesis{Viehmann2019,\n  author = {Viehmann, Tarik},\n  title = {Transforming Robotic Plans with Timed Automata to Solve Temporal Platform Constraints},\n  year = {2019},\n  month = dec,\n  school = {{RWTH Aachen University}},\n  type = {mathesis},\n  advisor = {Hofmann, Till},\n  url = {https://kbsg.rwth-aachen.de/~hofmann/theses/viehmann.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n Neural Combinatorial Optimization for Production Planning.\n \n \n \n\n\n \n Aymen Gannouni.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, December 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@thesis{Gannouni2019,\n  author      = {Aymen Gannouni},\n  title       = {Neural Combinatorial Optimization for Production Planning},\n  year        = {2019},\n  month       = dec,\n  school      = {{RWTH Aachen University}},\n  type        = {mathesis},\n  advisor     = {Behery, Mohamed},\n  abstract    = {Modern production processes rely on effective planning of resources, which deals with\n                 various combinatorial optimization problems. Many of these problems are NP-hard and\n                 constitute a challenging task to solve, especially for large instances. Neural combina-\n                 torial optimization has evolved as a field of research that tackle this task using recent\n                 advancements of machine learning, including deep reinforcement learning, and suggests\n                 competitive performance in comparison with commercial as well as open source solvers.\n                 Blown film extrusion, a practical case study of production scheduling with sequence-\n                 dependent setup costs, offers the chance to investigate the applicability, practicability,\n                 and scalability of neural combinatorial optimization in the context of production plan-\n                 ning. A prediction model, which estimates the waste generated by the set-up between\n                 a pair of products was built using regression, and served in measuring the optimization\n                 objective within the scope of the investigative study of neural combinatorial optimiza-\n                 tion.},\n  keywords    = {Production Scheduling, Combinatorial Optimization, Machine Learning, Deep Reinforcement Learning},\n  type        = {mathesis}\n}\n\n
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\n Modern production processes rely on effective planning of resources, which deals with various combinatorial optimization problems. Many of these problems are NP-hard and constitute a challenging task to solve, especially for large instances. Neural combina- torial optimization has evolved as a field of research that tackle this task using recent advancements of machine learning, including deep reinforcement learning, and suggests competitive performance in comparison with commercial as well as open source solvers. Blown film extrusion, a practical case study of production scheduling with sequence- dependent setup costs, offers the chance to investigate the applicability, practicability, and scalability of neural combinatorial optimization in the context of production plan- ning. A prediction model, which estimates the waste generated by the set-up between a pair of products was built using regression, and served in measuring the optimization objective within the scope of the investigative study of neural combinatorial optimiza- tion.\n
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\n \n\n \n \n \n \n \n Extracting action sequences from open-die forging observations.\n \n \n \n\n\n \n Matteo Tschesche.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, December 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@thesis{Tschesche2019,\n  author      = {Matteo Tschesche},\n  title       = {Extracting action sequences from open-die forging observations},\n  year        = {2019},\n  month       = dec,\n  school      = {{RWTH Aachen University}},\n  type        = {bathesis},\n  advisor     = {Behery, Mohamed},\n  abstract    = { Forging is a crucial process to form most of the metal products since the middle ages. In an open-die forging process, the metal is heated up and placed on a die by a robot arm. Afterwards another die is performing a sequence of passes in which it strikes the metal to the expected height. The plan of these sequences is called a pass schedule. While performing a pass, displacements of the metal have impact on the product quality. To improve the consistency of the robot control, an assistance system will be built, which needs to utilize the operator's expertise and a model of his or her behavior.\n This thesis explores three approaches for extracting action sequences from the observations collected during human operation. One approach is based on a Long Short Term Memory (LSTM) network \\citep{lstm_original}, a neural network which is able to store information for a long period of time. Another approach is based on an unsupervised segmentation algorithm called transition state clustering (TSC) \\citep{TSC} which is able to cluster noisy data. This thesis also provides a hysteresis thresholding approach, which has similarities to the Canny edge detector \\citep{canny}.},\n  keywords    = {Production Scheduling, Combinatorial Optimization, Machine Learning, Deep Reinforcement Learning}\n}\n\n
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\n Forging is a crucial process to form most of the metal products since the middle ages. In an open-die forging process, the metal is heated up and placed on a die by a robot arm. Afterwards another die is performing a sequence of passes in which it strikes the metal to the expected height. The plan of these sequences is called a pass schedule. While performing a pass, displacements of the metal have impact on the product quality. To improve the consistency of the robot control, an assistance system will be built, which needs to utilize the operator's expertise and a model of his or her behavior. This thesis explores three approaches for extracting action sequences from the observations collected during human operation. One approach is based on a Long Short Term Memory (LSTM) network i̧teplstm_original, a neural network which is able to store information for a long period of time. Another approach is based on an unsupervised segmentation algorithm called transition state clustering (TSC) i̧tepTSC which is able to cluster noisy data. This thesis also provides a hysteresis thresholding approach, which has similarities to the Canny edge detector i̧tepcanny.\n
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\n  \n 2017\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n Centralized Global Task Planning with Temporal Aspects on a Group of Mobile Robots in the RoboCup Logistics League.\n \n \n \n\n\n \n Matthias Löbach.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, 2017.\n \n\n\n\n
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@thesis{Lobach2017,\n  author = {Löbach, Matthias},\n  title = {Centralized Global Task Planning with Temporal Aspects on a Group of Mobile Robots in the RoboCup Logistics League},\n  year = {2017},\n  type = {mathesis},\n  school = {RWTH Aachen University},\n  advisor = {Niemueller, Tim}\n}\n\n
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\n \n\n \n \n \n \n \n A Document-Oriented Robot Memory for Knowledge Sharing and Hybrid Reasoning on Mobile Robots.\n \n \n \n\n\n \n Frederik Zwilling.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, 2017.\n \n\n\n\n
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@thesis{Zwilling2017,\n  author = {Zwilling, Frederik},\n  title = {A Document-Oriented Robot Memory for Knowledge Sharing and Hybrid Reasoning on Mobile Robots},\n  year = {2017},\n  type = {mathesis},\n  school = {RWTH Aachen University},\n  advisor = {Niemueller, Tim}\n}\n\n
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\n \n\n \n \n \n \n \n \n Generating Macro Actions from a Plan Database for Planning on Mobile Robots.\n \n \n \n \n\n\n \n Till Hofmann.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, 2017.\n \n\n\n\n
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@thesis{Hofmann2017,\n  author = {Hofmann, Till},\n  title = {Generating Macro Actions from a Plan Database for Planning on Mobile Robots},\n  year = {2017},\n  school = {RWTH Aachen University},\n  type = {mathesis},\n  advisor = {Niemueller, Tim},\n  url = {https://kbsg.rwth-aachen.de/~hofmann/theses/mathesis.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n Reasoning about Plausibility for the Winograd Schema Challenge.\n \n \n \n\n\n \n Denis Golovin.\n\n\n \n\n\n\n Master's thesis, Department of Computer Science, RWTH Aachen University, April 2017.\n \n\n\n\n
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@thesis{Golovin2017,\n  author      = {Denis Golovin},\n  title       = {Reasoning about Plausibility for the {Winograd}\n                  Schema Challenge},\n  school      = {Department of Computer Science, RWTH Aachen\n                  University},\n  year        = {2017},\n  month       = apr,\n  advisor     = {Cla{\\ss}en, Jens},\n  abstract    = {The Winograd Schema Challenge (WSC) has been proposed\n                  as an alternative to the Turing Test for measuring a\n                  machine's intelligence by letting it solve pronoun\n                  resolution problems that cannot be tackled by\n                  statistical analysis alone, but require commonsense,\n                  everyday background knowledge and some form of\n                  deeper "understanding" of the question. WSCs are\n                  thus hard to solve for machines, but easy for\n                  humans.  Many solutions so far are based on machine\n                  learning and natural language processing, and\n                  achieve results that are hardly better than\n                  guessing. Moreover, most knowledge-based approaches\n                  to the WSC have been purely theoretical. The goal of\n                  this thesis was to develop and implement a\n                  knowledge-based WSC solver. In particular, a logic\n                  of conditional beliefs called BO is employed that is\n                  capable of dealing with incomplete or even\n                  inconsistent information (which commonsense\n                  knowledge often is). It does so by formalising the\n                  observation that humans often reason by picturing\n                  different contingencies of what the world could be\n                  like, and then choose to believe what is thought to\n                  be most plausible. Relevant commonsense background\n                  information furthermore is obtained from the\n                  ConceptNet semantic network and translated into BO,\n                  and processed by the Limbo reasoner.},\n  type        = {mathesis}\n}\n\n
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\n The Winograd Schema Challenge (WSC) has been proposed as an alternative to the Turing Test for measuring a machine's intelligence by letting it solve pronoun resolution problems that cannot be tackled by statistical analysis alone, but require commonsense, everyday background knowledge and some form of deeper \"understanding\" of the question. WSCs are thus hard to solve for machines, but easy for humans. Many solutions so far are based on machine learning and natural language processing, and achieve results that are hardly better than guessing. Moreover, most knowledge-based approaches to the WSC have been purely theoretical. The goal of this thesis was to develop and implement a knowledge-based WSC solver. In particular, a logic of conditional beliefs called BO is employed that is capable of dealing with incomplete or even inconsistent information (which commonsense knowledge often is). It does so by formalising the observation that humans often reason by picturing different contingencies of what the world could be like, and then choose to believe what is thought to be most plausible. Relevant commonsense background information furthermore is obtained from the ConceptNet semantic network and translated into BO, and processed by the Limbo reasoner.\n
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\n \n\n \n \n \n \n \n \n A Knowledge-Based Activity Representation for Shared Autonomy Teleoperation of Robotic Arms.\n \n \n \n \n\n\n \n Mohamed Behery.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, 2016.\n \n\n\n\n
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@thesis{Behery2017,\n  author = {Behery, Mohamed},\n  title = {A Knowledge-Based Activity Representation for\nShared Autonomy Teleoperation of Robotic Arms},\n  year = {2016},\n  school = {{RWTH Aachen University}},\n  type = {mathesis},\n  advisor = {Schiffer, Stefan},\n  url = {https://github.com/Behery/behery.github.io/raw/master/thesis.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n \n Continual Planning and Execution Monitoring in the Agent Language Golog on a Mobile Robot.\n \n \n \n \n\n\n \n Till Hofmann.\n\n\n \n\n\n\n Bachelor's thesis, RWTH Aachen University, Aachen, Germany, 2015.\n \n\n\n\n
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@thesis{Hofmann2015,\n  title = {Continual Planning and Execution Monitoring in the Agent Language Golog on a Mobile Robot},\n  author = {Hofmann, Till},\n  year = {2015},\n  school = {RWTH Aachen University},\n  type = {bathesis},\n  advisor = {Niemueller, Tim},\n  address = {Aachen, Germany},\n  url = {https://kbsg.rwth-aachen.de/~hofmann/theses/bathesis.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n Towards Decidable Verification of Non-Terminating Golog Programs.\n \n \n \n\n\n \n Martin Liebenberg.\n\n\n \n\n\n\n Diploma thesis, Department of Computer Science, RWTH Aachen University, April 2013.\n \n\n\n\n
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@thesis{Liebenberg2013,\n  author      = {Martin Liebenberg},\n  title       = {Towards Decidable Verification of Non-Terminating\n                  {G}olog Programs},\n  school      = {Department of Computer Science, RWTH Aachen\n                  University},\n  year        = {2013},\n  month       = apr,\n  advisor     = {Cla{\\ss}en, Jens},\n  abstract    = {Claßen and Lakemeyer recently introduced algorithms\n                  for the verification of temporal properties of\n                  non-terminating Golog programs, based on the\n                  first-order modal Situation Calculus variant ES, and\n                  regression-based reasoning. However, while Golog’s\n                  high expressiveness is a desirable feature, it also\n                  means that their verification procedures cannot be\n                  guaranteed to terminate in general. In this thesis,\n                  we address this problem by showing that, for a\n                  relevant subset, the verification of non-terminating\n                  Golog programs is indeed decidable, which is\n                  achieved by means of three restrictions. First, we\n                  use the ES variant of a decidable two-variable\n                  fragment of the Situation Calculus that was\n                  introduced by Gu and Soutchanski. Second, we have to\n                  restrict the Golog program to contain ground action\n                  only. Finally, we consider special classes of\n                  successor state axioms, namely the context-free ones\n                  and those that only admit local effects.},\n  type        = {Diploma thesis}\n}\n\n
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\n Claßen and Lakemeyer recently introduced algorithms for the verification of temporal properties of non-terminating Golog programs, based on the first-order modal Situation Calculus variant ES, and regression-based reasoning. However, while Golog’s high expressiveness is a desirable feature, it also means that their verification procedures cannot be guaranteed to terminate in general. In this thesis, we address this problem by showing that, for a relevant subset, the verification of non-terminating Golog programs is indeed decidable, which is achieved by means of three restrictions. First, we use the ES variant of a decidable two-variable fragment of the Situation Calculus that was introduced by Gu and Soutchanski. Second, we have to restrict the Golog program to contain ground action only. Finally, we consider special classes of successor state axioms, namely the context-free ones and those that only admit local effects.\n
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\n  \n 2010\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Incorporating Domain-Dependent Knowledge into a Golog-based System – An Empirical Evaluation.\n \n \n \n\n\n \n Ziquan Zhu.\n\n\n \n\n\n\n Master's thesis, Department of Computer Science, RWTH Aachen University, May 2010.\n \n\n\n\n
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@thesis{Zhu2010,\n  author      = {Ziquan Zhu},\n  title       = {Incorporating Domain-Dependent Knowledge into a\n                  {G}olog-based System -- An Empirical Evaluation},\n  school      = {Department of Computer Science, RWTH Aachen\n                  University},\n  year        = {2010},\n  month       = may,\n  advisor     = {Cla{\\ss}en, Jens},\n  abstract    = {This thesis provides presents an embedding of Doherty\n                  and Kvarnström's TALplanner into Golog. For this\n                  purpose, as theoretical foundation, a mapping\n                  between Temporal Action Logics and an appropriately\n                  extended variant of the modal Situation Calculus ES\n                  is given and proved to be correct. Furthermore, the\n                  embedding is implemented into the IndiGolog\n                  framework and evaluated empirically.},\n  type        = {mathesis}\n}\n\n
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\n This thesis provides presents an embedding of Doherty and Kvarnström's TALplanner into Golog. For this purpose, as theoretical foundation, a mapping between Temporal Action Logics and an appropriately extended variant of the modal Situation Calculus ES is given and proved to be correct. Furthermore, the embedding is implemented into the IndiGolog framework and evaluated empirically.\n
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\n  \n 2009\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n A Declarative Semantics of a Subset of PDDL with Constraints and Preferences.\n \n \n \n\n\n \n Ji-Hyoung Han.\n\n\n \n\n\n\n Diploma thesis, Department of Computer Science, RWTH Aachen University, February 2009.\n \n\n\n\n
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@thesis{Han2009,\n  author      = {Ji-Hyoung Han},\n  title       = {A Declarative Semantics of a Subset of {PDDL} with\n                  Constraints and Preferences},\n  school      = {Department of Computer Science, RWTH Aachen\n                  University},\n  year        = {2009},\n  month       = feb,\n  advisor     = {Cla{\\ss}en, Jens},\n  abstract    = {The thesis presents an extension of the modal\n                  Situation Calculus variant ES by the features of\n                  constraints, preferences and derived\n                  predictaes. Based on this, a semantic mapping\n                  between the corresponding subset of the planning\n                  language PDDL and the newly extended ES is provided,\n                  serving as an alternative, declarative semantics for\n                  PDDL's meta-theoretic, state-transitional semantics\n                  as well as the basis of embedding such planners into\n                  Golog.},\n  type        = {Diploma thesis}\n}\n\n
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\n The thesis presents an extension of the modal Situation Calculus variant ES by the features of constraints, preferences and derived predictaes. Based on this, a semantic mapping between the corresponding subset of the planning language PDDL and the newly extended ES is provided, serving as an alternative, declarative semantics for PDDL's meta-theoretic, state-transitional semantics as well as the basis of embedding such planners into Golog.\n
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\n  \n 2008\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Detection and Recognition of Human Faces using Random Forests for a Mobile Robot.\n \n \n \n \n\n\n \n Vaishak Belle.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University, Aachen, 2008.\n \n\n\n\n
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@thesis{ belle_msthesis,\n  title    = {Detection and Recognition of Human Faces using Random Forests for a Mobile Robot},\n  author   = {Belle, Vaishak},\n  year     = {2008},\n  pages    = {112},\n  school   = {RWTH Aachen University},\n  type     = {mathesis},\n  address  = {Aachen},\n  keywords = {face recognition, machine learning},\n  urlPDF   = {http://kbsg.rwth-aachen.de/~belle/Downloads/papers/thesis-belle.pdf},\n}\n\n
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\n  \n 2006\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n A Declarative Semantics of a Subset of PDDL with Time and Concurrency.\n \n \n \n\n\n \n Yuxiao Hu.\n\n\n \n\n\n\n Master's thesis, Department of Computer Science, RWTH Aachen University, November 2006.\n \n\n\n\n
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@thesis{Hu2006,\n  author      = {Yuxiao Hu},\n  title       = {A Declarative Semantics of a Subset of {PDDL} with\n                  Time and Concurrency},\n  school      = {Department of Computer Science, RWTH Aachen\n                  University},\n  year        = {2006},\n  month       = nov,\n  advisor     = {Cla{\\ss}en, Jens},\n  abstract    = {The thesis presents an extension of the modal\n                  Situation Calculus variant ES by the features of\n                  numerics, time, concurrency, and coerciveness. Based\n                  on this, a semantic mapping between the temporal\n                  subset of the planning language PDDL and the newly\n                  extended ES is provided, serving as an alternative,\n                  declarative semantics for PDDL's meta-theoretic,\n                  state-transitional semantics as well as the basis of\n                  embedding temporal planners into Golog.},\n  type        = {mathesis}\n}\n\n
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\n The thesis presents an extension of the modal Situation Calculus variant ES by the features of numerics, time, concurrency, and coerciveness. Based on this, a semantic mapping between the temporal subset of the planning language PDDL and the newly extended ES is provided, serving as an alternative, declarative semantics for PDDL's meta-theoretic, state-transitional semantics as well as the basis of embedding temporal planners into Golog.\n
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\n \n\n \n \n \n \n \n Decision-Theoretic Planning in the Dynamic Logic $\\mathcal{E\\!S}$.\n \n \n \n\n\n \n Dominique Ziegelmayer.\n\n\n \n\n\n\n Diploma thesis, Department of Computer Science, RWTH Aachen University, July 2006.\n \n\n\n\n
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@thesis{Ziegelmayer2006,\n  author      = {Dominique Ziegelmayer},\n  title       = {Decision-Theoretic Planning in the Dynamic Logic\n                  $\\mathcal{E\\!S}$},\n  school      = {Department of Computer Science, RWTH Aachen\n                  University},\n  year        = {2006},\n  month       = jul,\n  advisor     = {Cla{\\ss}en, Jens},\n  abstract    = {The thesis presents a representation for\n                  decision-theoretic problems in the modal Situation\n                  Calculus variant ES. Based on this representation,\n                  different decision-theoretic variants of the agent\n                  programming language Golog are established, namely\n                  an online- and an off-line version of DT-Golog. For\n                  this purpose, a transition semantics for such\n                  programs is defined and prototype implementations\n                  have been developed.},\n  type = {Diploma thesis}\n}\n\n
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\n The thesis presents a representation for decision-theoretic problems in the modal Situation Calculus variant ES. Based on this representation, different decision-theoretic variants of the agent programming language Golog are established, namely an online- and an off-line version of DT-Golog. For this purpose, a transition semantics for such programs is defined and prototype implementations have been developed.\n
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\n  \n 2005\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n ReadyWorld - A Qualitative Worldmodel for Autonomous Soccer Agents in the ReadyLog Framework.\n \n \n \n \n\n\n \n Stefan Schiffer.\n\n\n \n\n\n\n Master's thesis, Knowledge-based Systems Group, RWTH Aachen University, 2005.\n \n\n\n\n
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@thesis{ Schiffer2005ReadyWorld,\n  title  = {ReadyWorld - A Qualitative Worldmodel for Autonomous Soccer Agents in the ReadyLog Framework},\n  author = {Schiffer, Stefan},\n  year   = {2005},\n  school = {Knowledge-based Systems Group, RWTH Aachen University},\n  type   = {mathesis},\n  urlPDF = {https://kbsg.rwth-aachen.de/sites/kbsg/files/schiffer2005thesis.pdf},\n}\n\n
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\n  \n 2003\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n Integrating decision-theoretic planning and programming for robot control in highly dynamic domains.\n \n \n \n\n\n \n Christian Fritz.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen University (Knowledge-based Systems Group), Aachen, Germany, 2003.\n \n\n\n\n
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@thesis{ Fritz2003DTP,\n  title = {Integrating decision-theoretic planning and programming for robot control in highly dynamic domains},\n  author = {Fritz, Christian},\n  year = {2003},\n  school = {RWTH Aachen University (Knowledge-based Systems Group)},\n  type = {mathesis},\n  address = {Aachen, Germany},\n  attachments = {https://kbsg.rwth-aachen.de/sites/kbsg/files/Fritz2003Integrating.pdf},\n}\n\n
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\n \n\n \n \n \n \n \n Die Entwicklung von Ähnlichkeitsmaßen für den Vergleich von Spielsituationen im RoboCup.\n \n \n \n\n\n \n Björn Riedel.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen, 2003.\n \n\n\n\n
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@thesis{ Riedel2003,\n  title = {Die Entwicklung von {\\"A}hnlichkeitsma{\\ss}en f{\\"u}r den Vergleich von Spielsituationen im {RoboCup}},\n  year = {2003},\n  school = {RWTH Aachen},\n  type = {mathesis},\n  author = {Riedel, Bj{\\"o}rn}\n}\n\n
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\n \n\n \n \n \n \n \n Eine Erweiterung des Agentenmodells in SNet um eine Planungskomponente unter Verwendung von Nutzentheorie.\n \n \n \n\n\n \n Dominik Schmitz.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen, 2003.\n \n\n\n\n
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@thesis{ Schmitz2003,\n  title = {Eine Erweiterung des Agentenmodells in {SNet} um eine Planungskomponente unter Verwendung von Nutzentheorie},\n  year = {2003},\n  school = {RWTH Aachen},\n  type = {mathesis},\n  author = {Schmitz, Dominik}\n}\n\n
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\n  \n 2002\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n A Binaural Sound Source Localization System for a Mobile Robot.\n \n \n \n\n\n \n Laurent Calmes.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen, 2002.\n \n\n\n\n
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@thesis{ Calmes2002Binaural,\n  title = {A Binaural Sound Source Localization System for a Mobile Robot},\n  year = {2002},\n  school = {RWTH Aachen},\n  type = {mathesis},\n  author = {Calmes, Laurent}\n}\n\n
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\n \n\n \n \n \n \n \n Einbindung einfacher Bildverarbeitungsverfahren in die Steuerungssoftware eines autonomen mobilen Roboters.\n \n \n \n\n\n \n Armin Karbiener.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen, 2002.\n \n\n\n\n
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@thesis{ Karbiener2002Diplom,\n  title = {Einbindung einfacher Bildverarbeitungsverfahren in die Steuerungssoftware eines autonomen mobilen Roboters},\n  year = {2002},\n  school = {RWTH Aachen},\n  type = {mathesis},\n  author = {Karbiener, Armin}\n}\n\n
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\n \n\n \n \n \n \n \n Entwurf eines Rahmenwerks zur Entwicklung von deliberativen Komponenten für unsichere, hochgradig dynamische Umgebungen mit Ec.\n \n \n \n\n\n \n Norman Jansen.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen, 2002.\n \n\n\n\n
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@thesis{ Jansen2002Diplom,\n  title = {Entwurf eines Rahmenwerks zur Entwicklung von deliberativen Komponenten f{\\"u}r unsichere, hochgradig dynamische Umgebungen mit Ec},\n  year = {2002},\n  school = {RWTH Aachen},\n  type = {mathesis},\n  author = {Jansen, Norman}\n}\n\n
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\n \n\n \n \n \n \n \n Erkennen und Anfahren einer aktiven Landmarke durch einen ressourcenbeschränkten mobilen Roboter.\n \n \n \n\n\n \n Olaf Fischer.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen, 2002.\n \n\n\n\n
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@thesis{ Fischer2002Diplom,\n  title = {Erkennen und Anfahren einer aktiven Landmarke durch einen ressourcenbeschr{\\"a}nkten mobilen Roboter},\n  year = {2002},\n  school = {RWTH Aachen},\n  type = {mathesis},\n  author = {Fischer, Olaf}\n}\n\n
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\n  \n 2000\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Entwurf einer robusten Sprachsteuerung für einen mobilen Roboter.\n \n \n \n\n\n \n Frank Dylla.\n\n\n \n\n\n\n Master's thesis, RWTH Aachen, 2000.\n \n\n\n\n
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@thesis{ Dylla2000Diplom,\n  title = {Entwurf einer robusten Sprachsteuerung f{\\"u}r einen mobilen Roboter},\n  year = {2000},\n  school = {RWTH Aachen},\n  type = {mathesis},\n  attachments = {https://kbsg.rwth-aachen.de/sites/kbsg/files/Dylla2000Entwurf.pdf},\n  author = {Dylla, Frank}\n}\n\n
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