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\n@article{\n title = {Checking Different Video Game Mechanics to Assess Cognitive Abilities in Groups with and without Emotional Problems},\n type = {article},\n year = {2024},\n volume = {12},\n id = {8889b798-dc64-3239-a4cf-781867eedfa2},\n created = {2024-04-25T10:21:15.692Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2024-04-25T10:21:15.692Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {This study assesses cognitive abilities through video games for entertainment (Blek, Edge, and Unpossible) that were programmed from scratch to record players’ behavior and the levels achieved in a sample without emotional problems and in one with emotional problems. The non-emotional-problem sample was recruited from three universities and two bachelor’s degree programs. The emotional-problem sample was recruited from two outpatient centers. The participants in the emotional-problem sample completed reduced versions of the ability tests and video games, as required by their emotional problems. Three subtests of the Differential Aptitude Test that assessed abstract reasoning, visuospatial reasoning, and perceptual speed were selected as ability tests. All participants were required to complete a mental health questionnaire (PROMIS) and a brief questionnaire on their gaming habits and previous experience with the video games used. The results that were obtained showed good convergent validity of the video games as measures of cognitive abilities, and they showed that the behavior of players in the sample without emotional problems while playing predicted the level achieved in the Blek and Unpossible game fragments, but this was only true for Unpossible in the emotional-problem sample; finally, shorter versions of the Blek and Edge game fragments can be used because they maintain their good psychometric properties.},\n bibtype = {article},\n author = {Román, Francisco J. and Gutiérrez, Pablo and Ramos-Cejudo, Juan and González-Calero, Pedro Antonio and Gómez-Martín, Pedro Pablo and Larroy, Cristina and Martín-Brufau, Ramón and López-Cavada, Carlos and Quiroga, María Ángeles},\n doi = {10.3390/jintelligence12010001},\n journal = {Journal of Intelligence},\n number = {1}\n}\n
@article{\n title = {On the Importance of Contextualizing an Educational Escape Room Activity},\n type = {article},\n year = {2024},\n pages = {43-56},\n volume = {22},\n month = {8},\n publisher = {Academic Conferences International Ltd},\n day = {28},\n id = {249f595c-34bf-3f79-bc2a-6b7716bfe7df},\n created = {2025-05-19T15:13:00.775Z},\n file_attached = {true},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2025-05-19T15:13:01.193Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {This paper describes the design and evaluation of "Enigma Bio", an educational escape room activity that aims to convey the abstract concept of biodiversity to children between 11 and 13 years of age, making them aware of the importance of climate change and its impact on biodiversity. The design of Enigma Bio is closely linked to the Biodiversity exhibition at the National Museum of Natural Sciences in Madrid, designed for a visit in groups of between 20 and 30 children, with an approximate duration of one hour, running on mobile devices and including augmented reality technology. The purpose of this research is to determine whether, in the case of educational escape room activities in museums with a limited time duration, it is more effective to have a pre-session introducing the topic. Our hypothesis is that without the context of the pre-explanation, the playful component of the game may be too powerful and may cause children not to pay enough attention to the message that the game intends to communicate, and even more so when dealing with a complex message such as the effect of climate change on biodiversity. To answer this research question, we follow an A/B testing experimental design involving two groups of children, one of which received an introductory talk on biodiversity and climate change before going to the museum and the other did not. The experimental design is completed with a pre-post evaluation of the children's environmental awareness by means of a previously validated questionnaire. The results of the experiment provide valuable insights into the effectiveness of the pre-session introduction in enhancing the learning outcomes of short educational escape room activities. Significant differences were observed between pre- and post-activity tests, indicating a moderate overall increase in awareness scores within both individual groups (A and B) as well as across the combined results. The findings suggest that the pre-session introduction indeed plays a role in enhancing students' awareness of the targeted message. These results represent a breakthrough in the e-learning practice that will be of value to other designers of educational escape rooms with a limited time duration.},\n bibtype = {article},\n author = {Gonzalez-Calero, Pedro Antonio and Camps-Ortueta, Irene and Gutiérrez-Sánchez, Pablo and Gómez-Martín, Pedro Pablo},\n doi = {10.34190/ejel.22.4.3199},\n journal = {Electronic Journal of e-Learning},\n number = {4}\n}\n
@article{\n title = {A Progress-Based Algorithm for Interpretable Reinforcement Learning in Regression Testing},\n type = {article},\n year = {2024},\n keywords = {Chatbots,Games,Logic,Reinforcement learning,Task analysis,Testing,Video games,automated game testing,game-playing AI,regression testing,reinforcement learning,temporal logics},\n publisher = {Institute of Electrical and Electronics Engineers Inc.},\n id = {191dd63c-3300-3e78-9656-f3b6bc0fde92},\n created = {2025-05-19T15:27:50.121Z},\n file_attached = {true},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2025-05-19T15:27:50.573Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {In video games, the validation of design specifications throughout the development process poses a major challenge as the project grows in complexity and scale and purely manual testing becomes very costly. This paper proposes a new approach to design validation regression testing based on a reinforcement learning technique guided by tasks expressed in a formal logic specification language (TLTL) and the progress made in completing these tasks. This requires no prior knowledge of machine learning to train testing bots, is naturally interpretable and debuggable, and produces dense reward functions without the need for reward shaping. We investigate the validity of our strategy by comparing it to an imitation baseline in experiments organized around three use cases of typical scenarios in commercial video games on a 3D stealth testing environment created in Unity. For each scenario, we analyze the agents' reactivity to modifications in common assets to accommodate design needs in other sections of the game, and their ability to report unexpected gameplay variations. Our experiments demonstrate the practicality of our approach for training bots to conduct automated regression testing in complex video game settings.},\n bibtype = {article},\n author = {Gutierrez-Sanchez, Pablo and Gomez-Martin, Marco A. and Gonzalez-Calero, Pedro A. and Gomez-Martin, Pedro P.},\n doi = {10.1109/TG.2024.3426601},\n journal = {IEEE Transactions on Games}\n}\n
@inproceedings{\n title = {Reinforcement Learning with Temporal Logic Specifications for Regression Testing NPCs in Video Games},\n type = {inproceedings},\n year = {2023},\n id = {ad2840c9-f48d-3708-80b1-bd6deef2916b},\n created = {2025-05-19T19:31:18.732Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2025-05-19T19:31:18.732Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Reinforcement learning (RL) is a promising strategy for the development of autonomous agents in various control and optimization contexts, including the generation of autonomous players in video games. However, designing these agents, and in particular their reward functions to perform sequential decision-making, can be challenging for most users and often require tedious trial-and-error processes until a satisfactory result is obtained. Consequently, these strategies are generally beyond reach for designers and quality control teams, who could potentially make use of them to generate automatic testing agents. This paper presents the application of reinforcement learning and behavioral descriptions given through a formal temporal logic task specification language (TLTL) for the design of NPCs that can be employed as surrogates for the player in such contexts. We argue that these techniques enable designers to naturally specify the way in which they would expect the final player to interact with a level and then generate a test that automatically verifies whether this strategy continues to be feasible throughout the development of the game. We include a series of experiments conducted on a custom 3D test environment developed in Unity3D that show that the proposed methodology provides a simple mechanism for training NPCs in settings that are commonly encountered in modern video games.},\n bibtype = {inproceedings},\n author = {Gutierrez-Sanchez, Pablo and Gomez-Martin, Marco A. and Gonzalez-Calero, Pedro A. and Gomez-Martin, Pedro P.},\n doi = {10.1109/CoG57401.2023.10333208},\n booktitle = {IEEE Conference on Computatonal Intelligence and Games, CIG}\n}\n
@article{\n title = {Measuring Control to Dynamically Induce Flow in Tetris},\n type = {article},\n year = {2022},\n volume = {14},\n id = {d49ff4f6-36dd-3b9d-9642-51d70bbfe21b},\n created = {2025-05-19T19:31:25.034Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2025-05-19T19:31:25.034Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Dynamic difficulty adjustment (DDA) is a set of techniques that aim to automatically adapt the difficulty of a video game based on the player's performance. This article presents a methodology for DDA using ideas from the theory of flow and case-based reasoning (CBR). In essence, we are looking to generate game sessions with a similar difficulty evolution to previous game sessions that have produced flow in players with a similar skill level. We propose a CBR approach to dynamically assess the player's skill level and adapt the difficulty of the game based on the relative complexity of the last game states. We develop a DDA system for Tetris using this methodology and show, in an experiment with 40 participants, that the DDA version has a measurable impact on the perceived flow using validated questionnaires.},\n bibtype = {article},\n author = {Lora-Ariza, Diana Sofia and Sanchez-Ruiz, Antonio A. and Gonzalez-Calero, Pedro Antonio and Camps-Ortueta, Irene},\n doi = {10.1109/TG.2022.3182901},\n journal = {IEEE Transactions on Games},\n number = {4}\n}\n
@inproceedings{\n title = {Reinforcement Learning Methods to Evaluate the Impact of AI Changes in Game Design},\n type = {inproceedings},\n year = {2021},\n keywords = {Behavior Trees (BTs),Reinforcement Learning (RL)},\n pages = {10-17},\n volume = {17},\n issue = {1},\n websites = {https://ojs.aaai.org/index.php/AIIDE/article/view/18885},\n id = {95e56358-4767-3fef-8dc6-a926505452c3},\n created = {2025-05-19T19:31:49.073Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2025-05-19T19:31:49.073Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Game development has become a long process that requires many professionals working on a project during several months or years. With this scenario the re-utilization of resources is crucial not only to alleviate the process but also to bring coherence into the final product. In this paper we focus on the reuse of NPCs and the problems it brings about. In particular it is common to have different breeds (or personalities) of NPCs that are placed on different levels on the game. The problem arises when their behaviors are fine-tuned to accommodate a specific level needs without taking into consideration that this change may alter their performance on previous already-tested levels. The paper presents the application of reinforcement learning together with behavior trees to automatically test if modifications to the AIs of a stealth game have an impact on the user experience. Our experiments reveal that this approach provides a way of diagnosing alterations in level gameplay that correspond to the effects observed by human testers.},\n bibtype = {inproceedings},\n author = {Gutiérrez-Sánchez, Pablo and Gómez-Martín, Marco A. and González-Calero, Pedro A. and Gómez-Martín, Pedro P.},\n booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment}\n}\n
@book{\n title = {Measuring Preferences in Game Mechanics: Towards Personalized Chocolate-Covered Broccoli},\n type = {book},\n year = {2019},\n source = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},\n keywords = {Augmented Reality,Games for education,Games in museums,Informal learning,Serious games},\n volume = {11863 LNCS},\n id = {d5ce47d6-06ea-30cf-a3ab-c3eaf37aa47a},\n created = {2021-11-06T07:11:06.376Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2021-11-06T07:11:06.376Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {© IFIP International Federation for Information Processing, 2019. When developing educational games we face the problem of finding the right design for making the learning activities as intrinsic to the game mechanics as possible. Nevertheless, in many cases it is not possible to fully integrate the learning content into the game play, resulting in the well known “chocolate-covered broccoli” game design. The long term goal of the work presented here is to determine whether a personalized selection of game mechanics for the playful part, the game mechanics around the learning part of the game, can improve the satisfaction of the player and therefore make the whole learning experience more enjoyable. The first step towards that goal is to obtain a model for the preferences of game mechanics for a particular type of game, and later use that model to guide the selection of game mechanics. In this paper, we present Enigma MNCN a treasure hunt for mobile devices designed for the National Museum of Natural Sciences of Spain and some experimental results intended to identify preferences for game mechanics in that type of game across demographic variables. The main finding of these experiments is that preferences in game mechanics get shadowed when combined with a mostly disliked learning mechanic.},\n bibtype = {book},\n author = {Camps-Ortueta, I. and González-Calero, P.A. and Quiroga, M.A. and Gómez-Martín, P.P.},\n doi = {10.1007/978-3-030-34644-7_2}\n}\n
@article{\n title = {Trained Behavior Trees: Programming by Demonstration to Support AI Game Designers},\n type = {article},\n year = {2017},\n pages = {5-14},\n volume = {11},\n id = {3f785d3f-cd57-3ab4-8f61-d778de93e390},\n created = {2019-05-16T09:42:44.590Z},\n file_attached = {true},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2019-05-16T09:42:48.211Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Programming by demonstration (PbD) has a straightforward application in the development of the artificial intelligence (AI) for non-player characters (NPCs) in a games: a game designer controls the NPC during a training session in the game, and thus demon- strates the expected behavior for that character in dif- ferent situations. Afterwards, applying some machine learning technique on the traces recorded during the demonstration, an AI for the NPC can be generated. Nevertheless, with this approach, it is very hard for the game designer to fully control the resulting behavior, which is a key requirement for game designers, who are responsible for putting together a fun experience for the player. In this paper, we present Trained Behavior Trees (TBTs). TBTs are behavior trees (BTs) generated from traces obtained in a game through programming by demonstration. BTs are a technique widely used for AI programming which are created and modified through special purpose visual editors. By inducing a BTs from a programming by demonstration game session, we combine the ease of use of this technique with the ability to fine-tune the learned behavior of BTs. Fur- thermore, TBTs facilitate the use of behavior trees by game designers and promote their authoring control on game AI},\n bibtype = {article},\n author = {Sagredo-Olivenza, Ismael and Gomez-Martin, Pedro Pablo and Gomez-Martin, Marco Antonio and Gonzalez-Calero, Pedro Antonio},\n doi = {10.1109/tg.2017.2771831},\n journal = {IEEE Transactions on Games},\n number = {1}\n}\n
@article{\n title = {Measuring similarity of individuals in description logics over the refinement space of conjunctive queries},\n type = {article},\n year = {2016},\n pages = {447-467},\n volume = {47},\n websites = {https://doi.org/10.1007/s10844-015-0374-3},\n id = {f83d77aa-93df-3d22-b90a-1fc1e34406f3},\n created = {2017-11-07T08:39:26.528Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2017-11-07T08:39:26.878Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {DBLP:journals/jiis/Sanchez-RuizOGP16},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Sánchez-Ruiz, Antonio A and Ontañón, Santiago and González-Calero, Pedro A and Plaza, Enric},\n doi = {10.1007/s10844-015-0374-3},\n journal = {J. Intell. Inf. Syst.},\n number = {3}\n}\n
@article{\n title = {Template-based design in COLIBRI studio},\n type = {article},\n year = {2014},\n keywords = {COLIBRI Studio,Case-Based Reasoning,Template-Based Design},\n pages = {168-178},\n volume = {40},\n id = {37df3657-a278-3d65-9ff1-dd10f581da5b},\n created = {2017-11-07T08:40:10.864Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2017-11-07T08:40:10.988Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Case-Based Reasoning (CBR) and software generation share a common conceptual model of reusing components to obtain new solutions. Based on this model, in this paper we describe a novel development process for generating CBR systems based on the idea of reusing previous system designs. Template-Based Design (TBD) is the most significant activity in this development process and defines several actors (researcher, developer, student, etc.) involved in the development process of CBR systems with different backgrounds, motivations and goals. The TBD activity is supported by several tools integrated into the COLIBRI Studio Development Environment. These tools rely on semantic descriptions of workflows and components by means of an ontology that supports the reasoning regarding the correctness of the application being generated. We claim that the conceptualization of system behavior into templates and its reuse through the TBD serves to reduce the development effort required to build CBR applications. Thus, we present an experimental evaluation of the viability of the approach. © 2012 Elsevier Ltd.},\n bibtype = {article},\n author = {Recio-García, J.A. and González-Calero, P.A. and Díaz-Agudo, B.},\n doi = {10.1016/j.is.2012.11.003},\n journal = {Information Systems}\n}\n
@article{\n title = {Supporting sketch-based retrieval from a library of reusable behaviours},\n type = {article},\n year = {2013},\n keywords = {AI authoring tools,Behaviour authoring,FSMs,Game design,Graph matching,Non-playing characters},\n pages = {531-542},\n volume = {40},\n id = {d42068e3-a358-3854-a28c-26a00d6b42e2},\n created = {2017-11-07T08:41:34.861Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2017-11-07T08:41:34.973Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Building the behaviour for non-player characters in a game is a complex collaborative task among AI designers and programmers. In this paper we present a visual authoring tool for game designers that supports behaviour reuse. We describe a visual editor, capable of storing, indexing, retrieving and reusing behaviours previously designed by AI programmers. One of the most notable features of our editor is its capability for sketch-based retrieval: searching in a repository for behaviours that are similar to the one the user is drawing, and making suggestions about how to complete it. As this process relies on graph behaviour comparison, in this paper, we describe different algorithms for graph comparison, and demonstrate, through empirical evaluation in a particular test domain, that we can provide structure-based similarity for graphs that preserves behaviour similarity and can be computed at reasonable cost. © 2012 Elsevier Ltd. All rights reserved.},\n bibtype = {article},\n author = {Flórez-Puga, G. and González-Calero, P.A. and Jiménez-Díaz, G. and Díaz-Agudo, B.},\n doi = {10.1016/j.eswa.2012.07.067},\n journal = {Expert Systems with Applications},\n number = {2}\n}\n
@article{\n title = {Wings: Intelligent workflow-based design of computational experiments},\n type = {article},\n year = {2011},\n keywords = {computational experiments,computer-supported discovery,experiment design,intelligent systems,software components,workflow management},\n pages = {62-72},\n volume = {26},\n id = {c5423b70-c0d8-336a-a68a-8e55cd473720},\n created = {2017-11-07T08:40:12.925Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2017-11-07T08:40:13.083Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {The Wings intelligent workflow system assists scientists with designing computational experiments by automatically tracking constraints and ruling out invalid designs, letting scientists focus on their experiments and goals. © 2011 IEEE.},\n bibtype = {article},\n author = {Gil, Y. and Ratnakar, V. and Kim, J. and González-Calero, P. and Groth, P. and Moody, J. and Deelman, E.},\n doi = {10.1109/MIS.2010.9},\n journal = {IEEE Intelligent Systems},\n number = {1}\n}\n
@book{\n title = {Empowering designers with libraries of self-validated query-enabled behaviour trees},\n type = {book},\n year = {2011},\n source = {Artificial Intelligence for Computer Games},\n pages = {55-81},\n id = {69a6663f-8367-3864-b6c6-e7531df65cd8},\n created = {2017-11-07T08:40:42.719Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2017-11-07T08:40:42.819Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Building the behaviour fornon-player characters (NPC) in a game is a collaborative effort betweenAI designers and programmers. Programmers provide to the designers with the building blocks for specifying behaviours in the game, and designers use some combination ofstate machines,scripting and visual languages to build complex behaviours by composing the basic pieces the programmers provide.Behaviour trees (BTs) are the technology of choice for AI programmers to build NPC behaviour. Although BTs can be naturally built using visual languages that require no programming, in general, they are considered too complex for being built by designers without a programming background. In this chapter, we propose a number of techniques for facilitating the collaborative work of behaviour design through BTs. We provide tools for creating and managing a library of reusable fragments of BTs, intended for both programmers and designers. Such library is accessed through retrieval mechanisms that also support the definition of query nodes in BTs that can be expanded at run-time. In order to harness such an expressive power in behaviour design, we also propose an extension to the component-based architecture that supports a number of sanity checks to validate BTs, both at design and run-time. © 2011 Springer Science+Business Media, LLC.},\n bibtype = {book},\n author = {Flórez-Puga, G. and Llansó, D. and Gómez-Martín, M.A. and Gómez-Martín, P.P. and Díaz-Agudo, B. and González-Calero, P.A.},\n doi = {10.1007/978-1-4419-8188-2_3}\n}\n
@article{\n title = {Query-enabled behavior trees},\n type = {article},\n year = {2009},\n keywords = {Behavior trees (BTs),Case-based reasoning (CBR),First-person shooter (FPS),Nonplayer characters (NPCs)},\n pages = {298-308},\n volume = {1},\n id = {aa5fc032-130b-3d6e-808f-b50529c8b209},\n created = {2017-11-07T08:40:38.485Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2017-11-07T08:40:38.804Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Artificial intelligence in games is typically used for creating player's opponents. Manual editing of intelligent behaviors for nonplayer characters (NPCs) of games is a cumbersome task that needs experienced designers. Our research aims to assist designers in this task. Behaviors typically use recurring patterns, so that experience and reuse are crucial aspects for behavior design. The use of hierarchical structures like hierarchical state machines, behavior trees (BTs), or hierarchical task networks, allows working on different abstraction levels reusing pieces from the more detailed levels. However, the static nature of the design process does not release the designer from the burden of completely specifying each behavior. Our approach applies case-based reasoning (CBR) techniques to retrieve and reuse stored behaviors represented as BTs. In this paper, we focus on dynamic retrieval and selection of behaviors taking into account the world state and the underlying goals. The global behavior of the NPC is dynamically built at runtime querying the CBR system. We exemplify our approach through a serious game, developed by our research group, with gameplay elements from first-person shooter (FPS) games.},\n bibtype = {article},\n author = {Flórez-Puga, G. and Gómez-Martín, M.A. and Gómez-Martín, P.P. and Díaz-Agudo, B. and González-Calero, P.A.},\n doi = {10.1109/TCIAIG.2009.2036369},\n journal = {IEEE Transactions on Computational Intelligence and AI in Games},\n number = {4}\n}\n
@article{\n title = {Semantic templates for case-based reasoning systems},\n type = {article},\n year = {2009},\n pages = {245-264},\n volume = {24},\n id = {3faaa849-aa52-3b4a-ab6a-5fabcf643356},\n created = {2017-11-07T08:41:51.805Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2017-11-07T08:41:51.911Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {In this paper, we present an approach to solve the drawbacks of manual composition of software components. Our approach is applied within the jcolibri framework for building case-based reasoning (CBR) applications. We propose a system design process based on reusing templates obtained from previously designed CBR systems. Templates store the control flow of the CBR applications and include semantic annotations conceptualizing its behavior and expertise. We use CBR ontology to formalize syntactical, semantical and pragmatical aspects of the reusable components of the framework. The ontology vocabulary facilitates an annotation process of the components and allows to reason about their composition, facilitating the semi-automatic configuration of complex systems from their composing pieces. © 2009 Copyright Cambridge University Press.},\n bibtype = {article},\n author = {Recio-García, J.A. and Daz-Agudo, B. and González-Calero, P.A.},\n doi = {10.1017/S0269888909990051},\n journal = {Knowledge Engineering Review},\n number = {3}\n}\n
@article{\n title = {Teaching GoF design patterns through refactoring and role-play},\n type = {article},\n year = {2008},\n keywords = {Active learning,Object-oriented design pattern learning,Pattern-directed refactoring,Role-play},\n pages = {717-728},\n volume = {24},\n id = {af3d558e-d5f5-35b2-b726-18b079db6a35},\n created = {2017-11-07T08:40:31.504Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2017-11-07T08:40:31.602Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {In order to fully understand the implications of object-oriented design patterns, students need to consider alternative designs to a problem and to analyse these solutions in terms of coupling, cohesion and extensibility. Lecture-based approaches to teaching design patterns do not provide students with the insights needed unless they already have experience in object-oriented design. In this paper we present an approach to teaching design patterns that promotes active learning and makes students participate in refactorings through role-play sessions. We describe two experiments that demonstrate student acceptance and present promising results on the effectiveness of the approach. © 2008 TEMPUS Publications.},\n bibtype = {article},\n author = {Jiménez-Díaz, G. and Gómez-Albarrán, M. and González-Calero, P.A.},\n journal = {International Journal of Engineering Education},\n number = {4}\n}\n
@article{\n title = {Building CBR systems with jcolibri},\n type = {article},\n year = {2007},\n keywords = {Case-based reasoning,Ontologies,Problem-solving methods},\n pages = {68-75},\n volume = {69},\n id = {28801979-0b90-3fbd-a9b5-ff6d84c96a31},\n created = {2017-11-07T08:41:41.254Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2017-11-07T08:41:41.387Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Case-based reasoning (CBR) is a paradigm for combining problem solving and learning that has become one of the most successful applied subfields of AI in recent years. Now that CBR has become a mature and established technology two necessities have become critical: the availability of tools to build CBR systems, and the accumulated practical experience of applying CBR techniques to real-world problems. In this paper we are presenting jcolibri, an object-oriented framework in Java for building CBR systems, that greatly benefits from the reuse of previously developed CBR systems. © 2007 Elsevier B.V. All rights reserved.},\n bibtype = {article},\n author = {Díaz-Agudo, B. and González-Calero, P.A. and Recio-García, J.A. and Sánchez-Ruiz-Granados, A.A.},\n doi = {10.1016/j.scico.2007.02.004},\n journal = {Science of Computer Programming},\n number = {1-3}\n}\n
@article{\n title = {Formal concept analysis as a support technique for CBR},\n type = {article},\n year = {2001},\n keywords = {Case retrieval,Formal concept analysis,Galois lattices},\n pages = {163-171},\n volume = {14},\n id = {55e2368c-8eaf-35a4-a2e1-41fa791a22f7},\n created = {2017-11-07T08:41:19.282Z},\n file_attached = {false},\n profile_id = {7ff3d559-34c5-3dc7-a15e-4809d39e6685},\n group_id = {42178b72-b294-3d2f-9512-ce9371d745ab},\n last_modified = {2017-11-07T08:41:19.373Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {This paper shows how the use of Galois lattices and formal concept analysis (FCA) can support CBR application designers, in the task of discovering knowledge embedded in the cases. FCA applied on a case library provides an internal sight of the conceptual structure and allows finding patterns, regularities and exceptions among the cases. Moreover, it extracts certain dependence rules between the attributes describing the cases, that will be used to guide the query formulation process. © 2001 Elsevier Science B.V.},\n bibtype = {article},\n author = {Díaz-Agudo, B. and González-Calero, P.A.},\n doi = {10.1016/S0950-7051(01)00093-4},\n journal = {Knowledge-Based Systems},\n number = {3-4}\n}\n