EXAR: A Unified Experience-Grounded Agentic Reasoning Architecture. Bergmann, R., Brand, F., Lenz, M., & Malburg, L. In Bichindaritz, I. & López, B., editors, Case-Based Reasoning Research and Development, volume 15662, of Lecture Notes in Computer Science, pages 3–17, Cham, 2025. Springer Nature Switzerland.
Paper doi abstract bibtex 9 downloads Current AI reasoning often relies on static pipelines (like the 4R cycle from Case-Based Reasoning (CBR) or standard Retrieval-Augmented Generation (RAG)) that limit adaptability. We argue it is time for a shift towards dynamic, experience-grounded agentic reasoning. This paper proposes EXAR, a new unified, experience-grounded architecture, conceptualizing reasoning not as a fixed sequence, but as a collaborative process orchestrated among specialized agents. EXAR integrates data and knowledge sources into a persistent Long-Term Memory utilized by diverse reasoning agents, which coordinate themselves via a Short-Term Memory. Governed by an Orchestrator and Meta Learner, EXAR enables flexible, context-aware reasoning strategies that adapt and improve over time, offering a blueprint for next-generation AI.
@inproceedings{Bergmann2025EXARUnifiedExperienceGrounded,
title = {{{EXAR}}: {{A Unified Experience-Grounded Agentic Reasoning Architecture}}},
shorttitle = {{{EXAR}}},
booktitle = {Case-{{Based Reasoning Research}} and {{Development}}},
author = {Bergmann, Ralph and Brand, Florian and Lenz, Mirko and Malburg, Lukas},
editor = {Bichindaritz, Isabelle and L{\'o}pez, Beatriz},
year = {2025},
series = {Lecture {{Notes}} in {{Computer Science}}},
volume = {15662},
pages = {3--17},
publisher = {Springer Nature Switzerland},
address = {Cham},
doi = {10.1007/978-3-031-96559-3_1},
abstract = {Current AI reasoning often relies on static pipelines (like the 4R cycle from Case-Based Reasoning (CBR) or standard Retrieval-Augmented Generation (RAG)) that limit adaptability. We argue it is time for a shift towards dynamic, experience-grounded agentic reasoning. This paper proposes EXAR, a new unified, experience-grounded architecture, conceptualizing reasoning not as a fixed sequence, but as a collaborative process orchestrated among specialized agents. EXAR integrates data and knowledge sources into a persistent Long-Term Memory utilized by diverse reasoning agents, which coordinate themselves via a Short-Term Memory. Governed by an Orchestrator and Meta Learner, EXAR enables flexible, context-aware reasoning strategies that adapt and improve over time, offering a blueprint for next-generation AI.},
isbn = {978-3-031-96559-3},
langid = {english},
url = {https://www.wi2.uni-trier.de/shared/publications/Bergmann2025EXARUnifiedExperienceGrounded.pdf}
}
Downloads: 9
{"_id":"hsCYNJYg5uERyQrX8","bibbaseid":"bergmann-brand-lenz-malburg-exaraunifiedexperiencegroundedagenticreasoningarchitecture-2025","author_short":["Bergmann, R.","Brand, F.","Lenz, M.","Malburg, L."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","title":"EXAR: A Unified Experience-Grounded Agentic Reasoning Architecture","shorttitle":"EXAR","booktitle":"Case-Based Reasoning Research and Development","author":[{"propositions":[],"lastnames":["Bergmann"],"firstnames":["Ralph"],"suffixes":[]},{"propositions":[],"lastnames":["Brand"],"firstnames":["Florian"],"suffixes":[]},{"propositions":[],"lastnames":["Lenz"],"firstnames":["Mirko"],"suffixes":[]},{"propositions":[],"lastnames":["Malburg"],"firstnames":["Lukas"],"suffixes":[]}],"editor":[{"propositions":[],"lastnames":["Bichindaritz"],"firstnames":["Isabelle"],"suffixes":[]},{"propositions":[],"lastnames":["López"],"firstnames":["Beatriz"],"suffixes":[]}],"year":"2025","series":"Lecture Notes in Computer Science","volume":"15662","pages":"3–17","publisher":"Springer Nature Switzerland","address":"Cham","doi":"10.1007/978-3-031-96559-3_1","abstract":"Current AI reasoning often relies on static pipelines (like the 4R cycle from Case-Based Reasoning (CBR) or standard Retrieval-Augmented Generation (RAG)) that limit adaptability. We argue it is time for a shift towards dynamic, experience-grounded agentic reasoning. This paper proposes EXAR, a new unified, experience-grounded architecture, conceptualizing reasoning not as a fixed sequence, but as a collaborative process orchestrated among specialized agents. EXAR integrates data and knowledge sources into a persistent Long-Term Memory utilized by diverse reasoning agents, which coordinate themselves via a Short-Term Memory. Governed by an Orchestrator and Meta Learner, EXAR enables flexible, context-aware reasoning strategies that adapt and improve over time, offering a blueprint for next-generation AI.","isbn":"978-3-031-96559-3","langid":"english","url":"https://www.wi2.uni-trier.de/shared/publications/Bergmann2025EXARUnifiedExperienceGrounded.pdf","bibtex":"@inproceedings{Bergmann2025EXARUnifiedExperienceGrounded,\n title = {{{EXAR}}: {{A Unified Experience-Grounded Agentic Reasoning Architecture}}},\n shorttitle = {{{EXAR}}},\n booktitle = {Case-{{Based Reasoning Research}} and {{Development}}},\n author = {Bergmann, Ralph and Brand, Florian and Lenz, Mirko and Malburg, Lukas},\n editor = {Bichindaritz, Isabelle and L{\\'o}pez, Beatriz},\n year = {2025},\n series = {Lecture {{Notes}} in {{Computer Science}}},\n volume = {15662},\n pages = {3--17},\n publisher = {Springer Nature Switzerland},\n address = {Cham},\n doi = {10.1007/978-3-031-96559-3_1},\n abstract = {Current AI reasoning often relies on static pipelines (like the 4R cycle from Case-Based Reasoning (CBR) or standard Retrieval-Augmented Generation (RAG)) that limit adaptability. We argue it is time for a shift towards dynamic, experience-grounded agentic reasoning. This paper proposes EXAR, a new unified, experience-grounded architecture, conceptualizing reasoning not as a fixed sequence, but as a collaborative process orchestrated among specialized agents. EXAR integrates data and knowledge sources into a persistent Long-Term Memory utilized by diverse reasoning agents, which coordinate themselves via a Short-Term Memory. Governed by an Orchestrator and Meta Learner, EXAR enables flexible, context-aware reasoning strategies that adapt and improve over time, offering a blueprint for next-generation AI.},\n isbn = {978-3-031-96559-3},\n langid = {english},\n url = {https://www.wi2.uni-trier.de/shared/publications/Bergmann2025EXARUnifiedExperienceGrounded.pdf}\n}\n\n\n","author_short":["Bergmann, R.","Brand, F.","Lenz, M.","Malburg, L."],"editor_short":["Bichindaritz, I.","López, B."],"key":"Bergmann2025EXARUnifiedExperienceGrounded","id":"Bergmann2025EXARUnifiedExperienceGrounded","bibbaseid":"bergmann-brand-lenz-malburg-exaraunifiedexperiencegroundedagenticreasoningarchitecture-2025","role":"author","urls":{"Paper":"https://www.wi2.uni-trier.de/shared/publications/Bergmann2025EXARUnifiedExperienceGrounded.pdf"},"metadata":{"authorlinks":{}},"downloads":9},"bibtype":"inproceedings","biburl":"https://web.wi2.uni-trier.de/publications/WI2Publikationen.bib","dataSources":["MSp3DzP4ToPojqkFy","J3orK6zvpR7d8vDmC"],"keywords":[],"search_terms":["exar","unified","experience","grounded","agentic","reasoning","architecture","bergmann","brand","lenz","malburg"],"title":"EXAR: A Unified Experience-Grounded Agentic Reasoning Architecture","year":2025,"downloads":9}