HICMA: A human imitating cognitive modeling agent using statistical methods and evolutionary computation

Intelligent agents are becoming more sophisticated than ever. An intelligent agent (IA) interacts with the environment. It takes observations through sensors and acts on the environment through actuators for achieving some goals. An IA usually keeps models for the environment and the interesting objects in this environment. These models are adapted according to the environmental changes. Wide researches have been done on the techniques of building and tuning such models. This paper introduces the Human Imitating Cognitive Modeling Agent (HICMA) that combines different techniques for building and tuning appropriate models for dynamic environment objects. It is based on a proposed updated version of Minsky´s society of mind theory where society agents evaluate and evolve each other in a novel way. HICMA has been tested by allowing it to play Robocode against the two opponents Shadow 3.66d and Walls. Results show that HICMA´s evolved mathematical behavior models gracefully translate actual human behaviors.