Multi-Agent Systems

ISBN-13: 9783031432637 / Angielski / Miękka / 2023

Opis

This volume LNCS 14282 constitutes the refereed proceedings of the 20th European Conference EUMAS 2023, held in Naples, Italy, during September 2023.This volume includes 24 full papers and 5 short papers, carefully selected from 47 submissions. Additionally, the volume features 16 short papers, rigorously reviewed from 20 submissions for the PhD day. The conference focused on the theory and practice of autonomous agents and multi-agent systems, covering a wide range of topics. 

Spis treści

Multiple Attribute List Aggregation: Its Application to Democratic Playlist Editing.- On the Graph Theory of Majority Illusions.- Qualitative Uncertainty Reasoning in AgentSpeak.- JaKtA: BDI agent-oriented programming in pure Kotlin.- Integrating Ontologies and Cognitive Conversational Agents in On2Conv.- Exploiting Reward Machines with Deep Reinforcement Learning in Continuous Action Domains.- A Comprehensive Presentation of the Jadescript Agent-Oriented Programming Language.- Verifying Programs by Bounded Tree-width Behavior Graphs.- Behavioral QLTL.- Lorenzen-style strategies as proof-search strategies.- SHAPE: A Framework for Evaluating the Ethicality of Influence.- Modelling Group Performance in Educational Multiagent Systems: Introducing the CollabQuest Simulation Game.- Towards Developing an Agent-based Model of Price Competition in the European Pharmaceutical Parallel Trade Market.- Using a BDI Agent to Represent a Human on the Factory Floor of the ARIAC 2023 Industrial Automation Competition.- Symbolic LTLf Best-Effort Synthesis.-  Robust Explanations for Human-Neural Multi-agent Systems with Formal Verification.- LTLf Synthesis Under Environment Specifications for Reachability and Safety Properties.- Logic-based approximations of preferences.- A Comparative Analysis of Multi-Agent Simulation Platforms for Energy and Mobility Management.- Observational Preorders for Alternating Transition Systems.- Synthesising Reward Machines for Cooperative Multi-Agent Reinforcement Learning.- Adaptive Cognitive Agents: Updating Action Descriptions and Plans.- Pretty Good Strategies and Where to Find Them.- A multi-agent Sudoku using the wave function collapse.