08594nam 2200469 450 99646439730331620220331071407.03-030-82254-0(CKB)4100000011982798(MiAaPQ)EBC6680413(Au-PeEL)EBL6680413(PPN)258303638(EXLCZ)99410000001198279820220331d2021 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMulti-agent systems 18th European Conference, EUMAS 2021, Virtual Event, June 28-29, 2021, Revised selected papers /Ariel Rosenfeld, Nimrod Talmon (editors)Cham, Switzerland :Springer,[2021]©20211 online resource (292 pages)Lecture notes in computer science ;128023-030-82253-2 Intro -- Preface -- Organization -- Contents -- Ascending-Price Mechanism for General Multi-sided Markets -- 1 Introduction -- 1.1 Previous Work -- 1.2 Our Contribution -- 2 Formal Definitions -- 2.1 Agents and Categories -- 2.2 Trades and Gains -- 2.3 Mechanisms -- 2.4 Recipe Forests -- 3 Computing Optimal Trade -- 4 Ascending Auction Mechanism -- 4.1 General Description -- 4.2 Example Run -- 5 Ascending Auction Properties -- 6 Experiments -- 6.1 Agents' Values -- 6.2 Number of Deals and Gain from Trade -- References -- Governing Black-Box Agents in Competitive Multi-Agent Systems -- 1 Introduction -- 1.1 Motivation -- 1.2 Governance in Multi-Agent Systems -- 1.3 Overview of the Approach -- 1.4 Contribution -- 1.5 Structure -- 2 Existing Work -- 2.1 Classification and Scope -- 2.2 Relevant Related Work -- 3 Model -- 3.1 Agents and Environment -- 3.2 Governance -- 4 Governance Loop -- 4.1 Observation and Learning Step -- 4.2 Restriction of Action Spaces -- 4.3 Algorithm -- 4.4 Computational Complexity -- 5 Evaluation -- 5.1 Setup -- 5.2 Results -- 6 Conclusion -- 6.1 Summary -- 6.2 Future Work -- References -- Path and Action Planning in Non-uniform Environments for Multi-agent Pickup and Delivery Tasks -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation and Background -- 3.1 N-MAPD -- 3.2 Well-Formed N-MAPD -- 4 Path and Action Planning with Orientation -- 4.1 Two-Stage Action Planning (TSAP) -- 4.2 Conflict Resolution of Candidate Action Sequences (CRCAS) -- 4.3 Plan Modification Strategy -- 4.4 Flows of Task Selection and PAPO Processes -- 5 Experiments and Discussion -- 5.1 Experimental Setting -- 5.2 Exp. 1: Performance Comparison -- 5.3 Exp. 2: Characteristics of the PAPO -- 6 Conclusion -- References -- Revealed Preference Argumentation and Applications in Consumer Behaviour Analyses -- 1 Introduction -- 2 Argumentation Frameworks.3 Revealed Preference Theory -- 4 RPT in Argumentation -- 5 Revealed Preference Argumentation (RPA) Framework -- 6 RPA as a Complete Computational Framework for RPT-based Consumer Behaviour Analyses -- 7 Conclusions -- References -- Coordinating Multi-party Vehicle Routing with Location Congestion via Iterative Best Response -- 1 Introduction -- 2 Related Works -- 2.1 ML-VRPLC as a Multi-Party VRP -- 2.2 ML-VRPLC as an MAP Problem -- 2.3 ML-VRPLC as a Non-cooperative MAP Problem -- 3 Problem Description -- 4 Model Formulation -- 4.1 ML-VRPLC as a Strategic Game -- 5 Solution Approach -- 5.1 Iterative Best Response Algorithm -- 5.2 Best Response Computation -- 6 Experiments -- 6.1 Experimental Setup -- 6.2 Experimental Results -- 7 Conclusion and Future Works -- References -- Explaining Ridesharing: Selection of Explanations for Increasing User Satisfaction -- 1 Introduction -- 2 Related Work -- 3 The PBE Agent -- 4 The AXIS Agent -- 5 Experimental Design -- 6 Results -- 7 Conclusions and Future Work -- References -- Large-Scale, Dynamic and Distributed Coalition Formation with Spatial and Temporal Constraints -- 1 Introduction -- 2 Related Work -- 2.1 Incomplete Search-Based Algorithms -- 2.2 Realistic Test Frameworks -- 3 Problem Formulation -- 3.1 Definitions -- 3.2 Decision Variables -- 3.3 Constraints -- 3.4 Objective Function -- 4 A Scalable, Dynamic and Distributed CFSTP Algorithm -- 4.1 Reduction of the CFSTP to a DynDCOP -- 4.2 Distributed CTS -- 5 Empirical Evaluation in Dynamic Environments -- 5.1 Setup -- 5.2 Results -- 6 Conclusions -- References -- Convention Emergence with Congested Resources -- 1 Introduction -- 2 Related Work -- 3 Modelling Norm Emergence with Congested Actions -- 3.1 Actions and Congested Resources -- 3.2 Agent Types: Mapping Values to Rewards -- 3.3 Authority Preferences and Influence on Rewards.3.4 Agent Learning -- 4 Experimental Methodology -- 5 Results -- 5.1 Baseline Setting -- 5.2 Fixed-Strategy Agents -- 5.3 Manipulating Agents' Sensitivities -- 5.4 Manipulating Agents' Costs -- 6 Conclusions and Future Work -- References -- Aiming for Half Gets You to the Top: Winning PowerTAC 2020 -- 1 Introduction -- 2 Background and Related Work -- 2.1 The Power Trading Agent Competition -- 2.2 Past Agent Strategies -- 3 TUC-TAC's Architecture -- 3.1 An Interesting Equilibrium Strategy for Repeated Multiagent Zero-Sum Game Settings -- 3.2 The Retail Market Module -- 3.3 The Wholesale Market Module -- 3.4 Net Demand Predictor Module -- 4 Experiments and Results -- 4.1 PowerTAC 2020 Post-Tournament Analysis -- 4.2 Predictor Evaluation and Impact -- 5 Conclusions and Future Work -- References -- Parameterized Analysis of Assignment Under Multiple Preferences -- 1 Introduction -- 2 Preliminaries -- 3 Fixed-Parameter Tractability and ETH Based Bounds -- 4 NP Hardness -- 5 Non-existence of Polynomial Kernels -- 6 Conclusion and Future Research -- References -- Solid Semantics for Abstract Argumentation Frameworks and the Preservation of Solid Semantic Properties -- 1 Introduction -- 2 Preliminary -- 2.1 Abstract Argumentation -- 2.2 Integrity Constraints and Judgment Aggregation -- 3 Solid Admissibility -- 4 Solid Semantics -- 5 Preservation of Solid Semantic Properties -- 5.1 Preserving Solid Self-defence and Solid Admissibility -- 5.2 Preserving Solid Reinstatement and Solid Completeness -- 5.3 Preserving Solid Groundedness, Solid Preferredness and Solid Stability -- 6 Related Work -- 7 Conclusion and Future Work -- References -- Verification of Multi-layered Assignment Problems -- 1 Introduction -- 2 Preliminaries -- 3 Properties of the Concepts of Optimality -- 4 Fixed-Parameter Tractability -- 5 coNP-Hardness.6 Non-existence of Polynomial Kernels -- 7 Conclusion and Future Research -- References -- Logic and Model Checking by Imprecise Probabilistic Interpreted Systems -- 1 Introduction -- 2 Background -- 2.1 Markovian Models -- 2.2 Probabilistic Interpreted Systems -- 3 Imprecise Epistemic PCTL -- 3.1 EIPCTL Syntax -- 3.2 Semantics of EIPCTL -- 4 Model Checking -- 5 Example -- 6 Conclusions -- References -- On the Complexity of Predicting Election Outcomes and Estimating Their Robustness -- 1 Introduction -- 2 Preliminaries -- 3 Results -- 3.1 PPIC -- 3.2 Mallows -- 3.3 EDM -- 3.4 Corresponding Decision Problem -- 4 Further Related Work -- 5 Conclusion -- References -- Point Based Solution Method for Communicative IPOMDPs -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Communicative Interactive POMDPs -- 3.2 Belief Update in CIPOMDPs -- 3.3 Planning in CIPOMDPs -- 4 Approach -- 4.1 Message Space -- 4.2 Sincerity and Deception -- 4.3 Communication for POMDP (Level-0 CIPOMDP) -- 4.4 IPBVI-Comm Algorithm -- 5 Experiments and Results -- 5.1 Multi-agent Tiger Game -- 5.2 Results -- 5.3 Algorithm Performance -- 6 Discussion -- 6.1 Cooperative Scenario -- 6.2 Non-cooperative Scenarios -- 6.3 Uncertainty About the Opponent -- 7 Conclusion -- References -- A Decentralized Token-Based Negotiation Approach for Multi-Agent Path Finding -- 1 Introduction -- 2 Problem Statement -- 3 Proposed Approach -- 3.1 Token-Based Alternating Offers Protocol (TAOP) -- 3.2 Path-Aware Negotiation Strategy -- 4 Evaluation -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 5 Related Work -- 6 Conclusion -- References -- Author Index.Lecture notes in computer science ;12802.Multiagent systemsCongressesMultiagent systems006.3Rosenfeld ArielTalmon NimrodMiAaPQMiAaPQMiAaPQBOOK996464397303316Multi-Agent Systems1968350UNISA