@inproceedings{Bergmann2025EXARUnifiedExperienceGrounded,
  title = {{{EXAR}}: {{A Unified Experience-Grounded Agentic Reasoning Architecture}}},
  shorttitle = {{{EXAR}}},
  booktitle = {{Case-Based Reasoning Research and Development - 33rd International Conference, {ICCBR} 2025, Biarritz, France, June 30 - July 3, 2025, Proceedings}},
  author = {Bergmann, Ralph and Brand, Florian and Lenz, Mirko and Malburg, Lukas},
  editor = {Bichindaritz, Isabelle and Lopez, Beatriz},
  year = {2025},
  series = {Lecture {{Notes}} in {{Computer Science}}},
  publisher = {Springer.},
  note 		 = {{Accepted for Publication.}},
  abstract = {Current AI reasoning often relies on static pipelines (like the 4R cycle from Case-Based Reasoning (CBR) or standard RetrievalAugmented 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.},
  langid = {english}
}

{"_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 - 33rd International Conference, ICCBR 2025, Biarritz, France, June 30 - July 3, 2025, Proceedings","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":["Lopez"],"firstnames":["Beatriz"],"suffixes":[]}],"year":"2025","series":"Lecture Notes in Computer Science","publisher":"Springer.","note":"Accepted for Publication.","abstract":"Current AI reasoning often relies on static pipelines (like the 4R cycle from Case-Based Reasoning (CBR) or standard RetrievalAugmented 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.","langid":"english","bibtex":"@inproceedings{Bergmann2025EXARUnifiedExperienceGrounded,\n title = {{{EXAR}}: {{A Unified Experience-Grounded Agentic Reasoning Architecture}}},\n shorttitle = {{{EXAR}}},\n booktitle = {{Case-Based Reasoning Research and Development - 33rd International Conference, {ICCBR} 2025, Biarritz, France, June 30 - July 3, 2025, Proceedings}},\n author = {Bergmann, Ralph and Brand, Florian and Lenz, Mirko and Malburg, Lukas},\n editor = {Bichindaritz, Isabelle and Lopez, Beatriz},\n year = {2025},\n series = {Lecture {{Notes}} in {{Computer Science}}},\n publisher = {Springer.},\n note \t\t = {{Accepted for Publication.}},\n abstract = {Current AI reasoning often relies on static pipelines (like the 4R cycle from Case-Based Reasoning (CBR) or standard RetrievalAugmented 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 langid = {english}\n}\n\n","author_short":["Bergmann, R.","Brand, F.","Lenz, M.","Malburg, L."],"editor_short":["Bichindaritz, I.","Lopez, B."],"key":"Bergmann2025EXARUnifiedExperienceGrounded","id":"Bergmann2025EXARUnifiedExperienceGrounded","bibbaseid":"bergmann-brand-lenz-malburg-exaraunifiedexperiencegroundedagenticreasoningarchitecture-2025","role":"author","urls":{},"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://web.wi2.uni-trier.de/publications/PublicationsMalburg.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}