Engineering multi-agent systems 12th international workshop, EMAS 2024, Auckland, New Zealand, May 6-7, 2024 : revised selected papers

.- SPARKIT: A Mind Map-Based MAS for Idea Generation Support. .- Cooperative Multi-agent Approach for Automated Computer Game Testing. .- On the external concurrency of current BDI frameworks for MAS. .- SADMA: Scalable Asynchronous Distributed Multi-Agent Reinforcement Learning Training Framewor...

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Körperschaft: International Workshop on Engineering Multi-Agent Systems (VerfasserIn)
Weitere Verfasser: Briola, Daniela (HerausgeberIn), Cardoso, Rafael C. (HerausgeberIn), Logan, Brian (HerausgeberIn)
Format: UnknownFormat
Sprache:eng
Veröffentlicht: Cham Springer 2025
Schriftenreihe:Lecture notes in computer science 15152
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Zusammenfassung:.- SPARKIT: A Mind Map-Based MAS for Idea Generation Support. .- Cooperative Multi-agent Approach for Automated Computer Game Testing. .- On the external concurrency of current BDI frameworks for MAS. .- SADMA: Scalable Asynchronous Distributed Multi-Agent Reinforcement Learning Training Framework. .- Synergizing Trust and Autonomy: Gaia-X Enabled Multi-Agent Ecosystems for Advanced Freight Fleet Management. .- Cognitive Planning for Persuasive Multimodal Interaction. .- A Novel Bidding Strategy for PDAs using MCTS in Continuous Action Spaces. .- Jadex BDI Agents Integrated with MATSim for Autonomous Mobility on Demand. .- Towards Engineering Explainable Autonomous Systems. .- Enhancing Confidence of the vGOAL Interpreter Using SAT Solving. .- Agents for DDD --- Back and Forth.
This book constitutes the revised selected papers from the 12th International Workshop on Engineering Multi-Agent Systems, EMAS 2024, held in Auckland, New Zealand, during May 6-7, 2024. The 7 full papers and 4 short papers included in this book were carefully reviewed and selected from a total of 18 submissions. These papers focus on topics such as agent-oriented software engineering, programming multi-agent systems, declarative agent languages and technologies, artificial intelligence, and machine learning
Beschreibung:Literaturangaben
Beschreibung:xviii, 188 Seiten
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ISBN:9783031711510
978-3-031-71151-0