CELIBERTO, L. A.Reinaldo BianchiSANTOS, P. E.2022-01-122022-01-122016-10-12CELIBERTO, L. A.; BIANCHI, R.; SANTOS, P. E.; Transfer Learning Heuristically Accelerated Algorithm: A Case Study with Real Robots. Proceedings - 13th Latin American Robotics Symposium and 4th Brazilian Symposium on Robotics, LARS/SBR 2016, p. 311-316, Oct. 2016.https://repositorio.fei.edu.br/handle/FEI/3870© 2016 IEEE.Reinforcement Learning (RL) is a successful technique for learning the solutions of control problems from an agent's interaction in its domain. However, RL is known to be inefficient for real-world applications. In this paper we propose to use a combination of case-based reasoning (CBR) and heuristically accelerated reinforcement learning methods aiming to speed up a Reinforcement Learning algorithm in a transfer learning problem. We show results of applying this method on a robot soccer domain, where the use of the proposed method led to a significant improvement in the learning rate.Acesso RestritoArtigo de evento10.1109/LARS-SBR.2016.59Heuristically AcceleratedReinforcement LearningTransfer Learning