Agent-organized networks for dynamic team formation
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
A survey of multi-agent organizational paradigms
The Knowledge Engineering Review
Local strategy learning in networked multi-agent team formation
Autonomous Agents and Multi-Agent Systems
Coalition Formation: From Software Agents to Robots
Journal of Intelligent and Robotic Systems
A flexible and reasonable mechanism for self-interested agent team forming
Multiagent and Grid Systems - Negotiation and Scheduling Mechanisms for Multiagent Systems
Team Formation Strategies in a Dynamic Large-Scale Environment
Massively Multi-Agent Technology
Combining Job and Team Selection Heuristics
Coordination, Organizations, Institutions and Norms in Agent Systems IV
Multi-Agent Collaboration: A Satellite Constellation Case
Proceedings of the 2008 conference on STAIRS 2008: Proceedings of the Fourth Starting AI Researchers' Symposium
An Incremental Adaptive Organization for a Satellite Constellation
Organized Adaption in Multi-Agent Systems
A formal model for emerging coalitions under network influence in humanitarian relief coordination
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
IRI'09 Proceedings of the 10th IEEE international conference on Information Reuse & Integration
Fluctuated peer selection policy and its performance in large-scale multi-agent systems
Web Intelligence and Agent Systems
Learning and Meta-Learning for Coordination of Autonomous Unmanned VehiclesA Preliminary Analysis
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
AMT'10 Proceedings of the 6th international conference on Active media technology
Coalition formation for task allocation: theory and algorithms
Autonomous Agents and Multi-Agent Systems
Constant factor approximation algorithms for coalition structure generation
Autonomous Agents and Multi-Agent Systems
Verifying team formation protocols with probabilistic model checking
CLIMA'11 Proceedings of the 12th international conference on Computational logic in multi-agent systems
Dynamic team forming in self-interested multi-agent systems
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Deciding roles for efficient team formation by parameter learning
KES-AMSTA'12 Proceedings of the 6th KES international conference on Agent and Multi-Agent Systems: technologies and applications
A sociologically inspired heuristic for optimization algorithms: A case study on ant systems
Expert Systems with Applications: An International Journal
A coalition formation mechanism for trust and reputation-aware multi-agent systems
SBIA'12 Proceedings of the 21st Brazilian conference on Advances in Artificial Intelligence
Considering inter-task resource constraints in task allocation
Autonomous Agents and Multi-Agent Systems
Distributed protocols for multi-agent coalition formation: a negotiation perspective
AMT'12 Proceedings of the 8th international conference on Active Media Technology
Reorganization of Agent Networks with Reinforcement Learning Based on Communication Delay
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
A decision network based framework for multiagent coalition formation
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Large-scale cooperative task distribution on peer-to-peer networks
Web Intelligence and Agent Systems
Intelligent Decision Technologies
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The coalition formation problem has received a consierable amount of attention in recent years. In this work we present a novel distributed algorithm that returns a solution in polynomial time and the quality of the returned solution increases as agents gain more experience. Our solution utilizes an underlying organization to guide the coalition formation process. We use reinforcement learning techniques to optimize decisions made locally by agents in the organization. Experimental results are presented, showing the potential of our approach.