Adapting Behavior by Inductive Prediction in Soccer Agents

Abstract

This paper proposes new architecture of agent which adapts its behavior by predicting the results of actions and avoiding taking ones predicted to be failures shown in Fig. 1. Our agent consists of five parts: Observer, Planner, Actor which are same as those of basic agent and write perceiving information in the first-order formalism, Learner which acquires prediction rules using inductive logic programming (ILP), and Checker which predicts the result of an action selected by Planner and changes action if it seems to be failure. The agent classifies past actions into successes and failures, then it learns rules from them to assort the current action without information after taking it.