A Trust Case-Based Model Applied to Agents Collaboration

Abstract

This paper shows an approach for developing a method that uses Case-Based Reasoning (CBR) for calculating trust levels in agents' collaboration. The proposed development foresees all interactions between agents are considered in the updating process of general trust level. These collaborations are also stored in a CBR database. Each new interaction calculates a situational trust level based on similar cases. This trust level will be weighed against the global trust level, creating an indicator based on the requested collaboration without excluding the collaboration history.