Evaluating trust in multi-agents system through temporal difference leaning

Abstract

In any mission that requires cooperation and teamwork of multiple agents, it is vital that each agent is able to trust one another to accomplish the mission successfully. This work looks into incorporating the concept of trust in a multi agent environment, allowing agents to compute trust they have on each other. The proposed trust evaluation model called TD Trust model is developed by adapting temporal difference (TD) learning algorithm into its evaluation framework. The proposed trust model evaluates the trust of an agent based on experience gained from interaction among agents. The proposed model is then tested using simulation experiments and its performance is compared against the Secure Trust model, which is a comprehensive model reported in literature.