Autonomous Agents and Multiagent Systems

AAMAS 2017 Workshops, Visionary Papers, São Paulo, Brazil, May 8-12, 2017, Revised Selected Papers
Herausgegeben:Sukthankar, Gita; Rodriguez-Aguilar, Juan A.

• Broschiertes Buch

Produktbeschreibung

This book compiles the most visionary papers from 10 workshops held at the International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017, held in Sao Paulo, Brazil, in May 2017.

The 15 full papers presented in this volume were carefully reviewed and selected for inclusion in this volume. They deal with novel ideas proposing a change in the way research is currently carried out.

Produktdetails

• Lecture Notes in Computer Science 10643
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-319-71678-7
• 1st ed. 2017
• Seitenzahl: 256
• Erscheinungstermin: 26. November 2017
• Englisch
• Abmessung: 235mm x 155mm x 15mm
• Gewicht: 394g
• ISBN-13: 9783319716787
• ISBN-10: 3319716786
• Artikelnr.: 49555729

Inhaltsangabe

Competitive Belief Propagation to efficiently solve Complex Multi-Agent Negotiations with Network Structure.- Stable Configurations with (Meta) Punishing Agents.- KILT: a modelling approach based on participatory agent-based simulation of stylized socio-ecosystems to stimulate social learning with local stakeholders.- Vote Buying Through Decoy Ballots.- Efficient evaluation of influenza mitigation strategies using preventive bandits.- Adaptive Agents in Minecraft: A Hybrid Paradigm for Combining Domain Knowledge with Reinforcement Learning.- Budget Limited Trust-Aware Decision Making.-Max-sum Revisited; The Real Power of Damping.- A Realistic Dataset for the Smart Home Device Scheduling Problem for DCOPs.- Computers That Negotiate on Our Behalf: Major Challenges for Self-sufficient, Self-directed, and Interdependent Negotiating Agents.- A MaxSAT-Based Approach to the Team Composition Problem in a Classroom.- Heuristic Data Merging for Constructing Initial Agent Populations.- NormConflict Identification using Deep Learning.- Identifying affordances for modelling second order emergent phenomena with the WIT framework.- A Personal Medical Digital Assistant Agent for Supporting Human Operators in Emergency Scenarios.