Negotiating task decomposition and allocation using partial global planning
Distributed Artificial Intelligence (Vol. 2)
Using Decision Theory to Formalize Emotions in Multi-Agent Systems
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Task delegation using experience-based multi-dimensional trust
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Agent-based trust model involving multiple qualities
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
IEEE Intelligent Systems
Attitude Driven Team Formation using Multi-Dimensional Trust
IAT '07 Proceedings of the 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Challenges for trust, fraud and deception research in multi-agent systems
AAMAS'02 Proceedings of the 2002 international conference on Trust, reputation, and security: theories and practice
Soft security: isolating unreliable agents from society
AAMAS'02 Proceedings of the 2002 international conference on Trust, reputation, and security: theories and practice
A temporal policy for trusting information
Trusting Agents for Trusting Electronic Societies
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Multi-dimensional trustworthiness assessments have been shown significantly beneficial to agents when selecting appropriate teammates to achieve a given goal. Reliability, quality, availability, and timeliness define the behavioral constraints of the proposed multi-dimensional trust (MDT) model. Given the multi-dimensional trust model in this research, an agent learns to identify the most beneficial teammates given different situations by prioritizing each dimension differently. An agent's attitudes towards rewards, risks and urgency are used to drive an agent's prioritization of dimensions in a MDT model. Each agent is equipped with a reinforcement learning mechanism with clustering technique to identify its optimal set of attitudes and change its attitudes when the environment changes. Experimental results show that changing attitudes to give preferences for respective dimensions in the MDT, and consequently, teammate selection based on the situation offer a superior means of finding the best teammates for goal achievement.