Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
A Pheromone-Based Utility Model for Collaborative Foraging
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Construction of numerical potential fields with reactive agents
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
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We present a simple ant model that solves a discrete foraging problem. We provide simulations and a convergence analysis. We argue that the ant population computes the solutions of some optimal control problems and converges in some well defined sense. We also discuss the rate of convergence with respect to the number of ants: we give experimental and theoretical arguments that suggest that this rate is superlinear with respect to the number of agents.