Ant Search Strategies For Planning Optimization

In this paper a planning framework based on Ant Colony Optimization techniques is presented. It is well known that finding optimal solutions to planning problems is a very hard computational problem. Stochastic methods do not guarantee either optimality or completeness, but it has been proved that in many applications they are able to find very good, often optimal, solutions. We propose several approaches based both on backward and forward search over the state space, using several heuristics and testing different pheromone models in order to solve sequential optimization planning problems.

• Type: Conference
• Year: 2009
• Where: AIPS
• Authors: Marco Baioletti, Alfredo Milani, Valentina Poggioni, Fabio Rossi
• Keywords: AIPS 2009, Ant Colony Optimization, Artificial Intelligence, Hard Computational Problem, Planning Problems