On the Relationship between Learning Capability and the Boltzmann-Formula

In this paper a combined use of reinforcement learning and simulated annealing is treated. Most of the simulated annealing methods suggest using heuristic temperature bounds as the basis of annealing. Here a theoretically established approach tailored to reinforcement learning following Softmax action selection policy will be shown. An application example of agent-based routing will also be illustrated.

• Type: Conference
• Year: 2001
• Where: IEAAIE
• Authors: Péter Stefán, Laszlo Monostori
• Keywords: Artificial Intelligence, IEAAIE 2001, Reinforcement Learning, Simulated Annealing, Simulated Annealing Methods