Fuzzy Ant Colony Optimization for optimal control

Ant Colony Optimization (ACO) has proven to be a very powerful optimization heuristic for Combinatorial Optimization Problems. While being very successful for various NPcomplete optimization problems, ACO is not trivially applicable to control problems. In this paper a novel ACO algorithm is introduced for the automated design of optimal control policies for continuous-state dynamic systems. The so called Fuzzy ACO algorithm integrates the multi-agent optimization heuristic of ACO with a fuzzy partitioning of the state space of the system. A simulated control problem is presented to demonstrate the functioning of the proposed algorithm.