The Effect of Multiagent Interaction Strategy on the Performance of Ant Model

개미 모델 성능에서 다중 에이전트 상호작용 전략의 효과

  • 이승관 (가톨릭대학교 컴퓨터정보공학부)
  • Published : 2005.06.01

Abstract

One of the important fields for heuristics algorithm is how to balance between Intensificationand Diversification. Ant Colony System(ACS) is a new meta heuristics algorithm to solve hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem(TSP). In this paper, we propose Multi Colony Interaction Ant Model that achieves positive negative interaction through elite strategy divided by intensification strategy and diversification strategy to improve the performance of original ACS. And, we apply multi colony interaction ant model by this proposed elite strategy to TSP and compares with original ACS method for the performance.

Keywords

Ant Colony System(ACS);Intensification;Diversification;Multi Agent