The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
Exploiting hierarchical domain structure to compute similarity
ACM Transactions on Information Systems (TOIS)
Coordination Artifacts: Environment-Based Coordination for Intelligent Agents
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
A survey of multi-agent organizational paradigms
The Knowledge Engineering Review
A capabilities-based model for adaptive organizations
Autonomous Agents and Multi-Agent Systems
Artifacts in the A&A meta-model for multi-agent systems
Autonomous Agents and Multi-Agent Systems
Dynamic protocols for open agent systems
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Self-organising agent organisations
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Adaptation of organizational models for multi-agent systems based on max flow networks
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Effective use of organisational abstractions for confidence models
ESAW'06 Proceedings of the 7th international conference on Engineering societies in the agents world VII
Adaptive mechanisms of organizational structures in multi-agent systems
PRIMA'06 Proceedings of the 9th Pacific Rim international conference on Agent Computing and Multi-Agent Systems
A composite self-organisation mechanism in an agent network
WISE'11 Proceedings of the 12th international conference on Web information system engineering
A functional taxonomy for artifacts
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
Trust decision-making in multi-agent systems
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Self-organization in an agent network: A mechanism and a potential application
Decision Support Systems
Persuading agents to act in the right way: An incentive-based approach
Engineering Applications of Artificial Intelligence
Policies for role maintenance through incentives: how to keep agents on track
AT'13 Proceedings of the Second international conference on Agreement Technologies
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In Open Multi-Agent Systems (OMAS), deciding with whom to interact is a particularly difficult task for an agent, as repeated interactions with the same agents are scarce, and reputation mechanisms become increasingly unreliable. In this work, we present a coordination artifact which can be used by agents in an OMAS to take more informed decisions regarding partner selection, and thus to improve their individual utilities. This artifact monitors the interactions in the OMAS, evolves a role taxonomy, and assigns agents to roles based on their observed performance in different types of interactions. This information can be used by agents to better estimate the expected behaviour of potential counterparts in future interactions. We thus highlight the descriptive features of roles, providing expectations of the behaviour of agents in certain types of interactions, rather than their normative facets. We empirically show that the use of the artifact helps agents to select better partners for their interactions than selection processes based only on agents' own experience. This is especially significant for agents that are newcomers to the OMAS.