Self-organization through bottom-up coalition formation
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Organization-Based Cooperative Coalition Formation
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Review on Computational Trust and Reputation Models
Artificial Intelligence Review
Task delegation using experience-based multi-dimensional trust
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
A survey of multi-agent organizational paradigms
The Knowledge Engineering Review
An integrated trust and reputation model for open multi-agent systems
Autonomous Agents and Multi-Agent Systems
Methods for task allocation via agent coalition formation
Artificial Intelligence
Coalition formation for task allocation: theory and algorithms
Autonomous Agents and Multi-Agent Systems
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Most multi-agent systems engineering methodologies propose the clear definition of roles and organizations. However, in distributed environments where agents with distinct capabilities coexist and cooperate to solve problems, having a rigid organization structure makes the system less adaptable to changes and failures. Some of the approaches to deal with these difficulties include centralized coordination and planning and the use of homogeneous agent capabilities. These solutions oppose key benefits of multi-agent systems, especially the agents' autonomy to interact and organize freely. In this paper, a novel approach is proposed where agents form and dissolve coalitions in a service-oriented environment while maintaining their autonomy. This allows the agent society to adjust to the demand for services and react to failures. To achieve this flexibility, a coalition formation mechanism for trust and reputation-aware multi-agent systems is employed. As agents interact, they establish a network of trusted peers that allows them to form stable coalitions with reduced risk of failures. Agents can also expand this network by exploring new partnerships based on the reputation of unknown agents that are recommended by these known peers. Experiments were performed to evaluate the proposal, with positive results in environments up to fifty agents under varying service demand and failure rates.