Knowledge Extension for Agent Learning in MAS
Multi-agent system (MAS) requires coordination mechanisms to facilitate dynamic collaboration of the intelligent components, with the goal of meeting local and global objectives. This paper deals with the issue of using dynamic epistemic default logic to offer a natural way of communication policies for the management of inter-agent exchanges in MAS. We first explore the communication protocols in MAS that operate in dynamic and highly uncertain environments, and then we add the constrained default sets to realize the extension of dynamic epistemic logic theory and restrict the agent’s inference behavior via constrained epistemic default reasoning. We also specify and reason the characteristic of the dynamic updating when agent meets incompatible knowledge in the logical framework that show the usefulness of logical tools carried out in the dynamic process of information acquisition.
KeywordsDynamic epistemic logic Epistemic extension Agent learning MAS
This work is supported by the National Science Foundation for Post-doctoral Scientists of China (No. 2012M510235) and the Fundamental Research Funds for the Central Universities under Grant No.2011121049.
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