Towards Dynamic Epistemic Learning of Actions in Autonomic Multi-agent Systems

摘要

This paper introduces dynamic epistemic learning of actions to autonomic Multi-agent Systems for self-learning, planning and self-upgrading. This case study implements and tests a simulation in NetLogo to explore the interaction between planning and the increase of agents' knowledge about actions for goal-directed self-improving.