Designing a Reinforcement Learning-based Adaptive AI for Large-Scale Strategy Games - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2006

Designing a Reinforcement Learning-based Adaptive AI for Large-Scale Strategy Games

Vincent Corruble
Geber Ramalho
  • Fonction : Auteur

Résumé

This paper investigates the challenges posed by the application of reinforcement learning to large-scale strategy games. In this context, we present steps and techniques which synthesize new ideas with state-of-the-art techniques from several areas of machine learning in a novel integrated learning approach for this kind of games. The performance of the approach is demonstrated on the task of learning valuable game strategies for a commercial wargame.
Fichier non déposé

Dates et versions

hal-01351276 , version 1 (03-08-2016)

Identifiants

  • HAL Id : hal-01351276 , version 1

Citer

Charles Madeira, Vincent Corruble, Geber Ramalho. Designing a Reinforcement Learning-based Adaptive AI for Large-Scale Strategy Games. AAAI conference on Artificial Intelligence and Interactive Digital Entertainement, Jun 2006, Marina del Rey, California, United States. pp.121-123. ⟨hal-01351276⟩
55 Consultations
0 Téléchargements

Partager

Gmail Mastodon Facebook X LinkedIn More