Using Multi-objective Optimization to Generate Timely Responsive BDI Agents

Abstract

A BDI agent’s ability to perform well depends on its reasoning time.If the reasoning is slow, it is possible that the environment has changed and the action selected is no longer optimal by the time the agent has finished to deliberate. This work then builds a BDI architecture using Anytime Algorithms that can control the amount of time used by the agent to reason and act on the environment. I briefly describe the proposed architecture and its implementation in the Jason agent language.