Reinforcement Learning Accelerated With Artificial Neural Network for Maze and Search Problems
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Dosyalar
Tarih
2010
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Reinforcement learning is the problem faced by an agent that must learn behaviour through trial and error interactions with a dynamic environment that lacks the educational examples. Q-learning is one of the most popular algorithms among the reinforcement learning methods. Artificial neural network, as in reinforcement learning, is a sub-entry of machine learning, which can be applied on real frames, the environment of which we do not have sufficient information. Our aim is to enable an autonomous agent placed in a maze to find the shortest path to the target by combining q learning and artificial neural network.
Açıklama
3rd Annual International Conference on Human System Interaction (HSI) -- MAY 13-15, 2010 -- Rzeszow, POLAND
Anahtar Kelimeler
Artificial neural networks, Maze and search problems, Q-learning, Reinforcement learning
Kaynak
3rd International Conference on Human System Interaction
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Hacıbeyoğlu, M., Arslan, A., (2010). Reinforcement Learning Accelerated With Artificial Neural Network for Maze and Search Problems. 3rd International Conference on Human System Interaction, 124-127.
