Results 11 to 20 of about 683,294 (301)

Reinforcement Learning: A Survey [PDF]

Journal of Artificial Intelligence Research, 1996
This paper surveys the field of reinforcement learning from a computer-science perspective. It is written to be accessible to researchers familiar with machine learning.
Kaelbling, L. P., Littman, M. L., Moore, A. W.   +2 more
core   +12 more sources

Reinforcement Learning

, 2020
Chapter in "A Guided Tour of Artificial Intelligence Research ...
Buffet, Olivier, Pietquin, Olivier, Weng, Paul   +2 more
  +5 more sources

Relational reinforcement learning [PDF]

Machine Learning, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dzeroski, Saso, De Raedt, Luc, Blockeel, Hendrik   +2 more
openaire   +6 more sources

Reinforcement Symbolic Learning [PDF]

, 2021
Complex problem solving involves representing structured knowledge, reasoning and learning, all at once. In this prospective study, we make explicit how a reinforcement learning paradigm can be applied to a symbolic representation of a concrete problem-solving task, modeled here by an ontology.
Mercier, Chloé, Alexandre, Frédéric, Viéville, Thierry   +2 more
openaire   +3 more sources

Effort reinforces learning

The Journal of Neuroscience, 2021
Humans routinely learn the value of actions by updating their expectations based on past outcomes – a process driven by reward prediction errors (RPEs). Importantly, however, implementing a course of action also requires the investment of effort. Recent work has revealed a close link between the neural signals involved in effort exertion and those ...
Huw Jarvis, Isabelle Stevenson, Amy Q. Huynh, Emily Babbage, James Coxon, Trevor T.-J. Chong   +5 more
openaire   +4 more sources

A Survey on Reinforcement Learning Methods in Bionic Underwater Robots

Biomimetics, 2023
Bionic robots possess inherent advantages for underwater operations, and research on motion control and intelligent decision making has expanded their application scope.
Ru Tong, Yukai Feng, Jian Wang, Zhengxing Wu, Min Tan, Junzhi Yu   +5 more
doaj   +1 more source

Feasibility Analysis and Application of Reinforcement Learning Algorithm Based on Dynamic Parameter Adjustment

Algorithms, 2020
Reinforcement learning, as a branch of machine learning, has been gradually applied in the control field. However, in the practical application of the algorithm, the hyperparametric approach to network settings for deep reinforcement learning still ...
Menglin Li, Xueqiang Gu, Chengyi Zeng, Yuan Feng   +3 more
doaj   +1 more source

Review of Model-Based Reinforcement Learning

Jisuanji kexue yu tansuo, 2020
Deep reinforcement learning (DRL) as an important learning paradigm in the field of machine learning, has received increasing attentions after AlphaGo defeats the human.
ZHAO Tingting, KONG Le, HAN Yajie, REN Dehua, CHEN Yarui
doaj   +1 more source

Performance characterization of reinforcement learning-enabled evolutionary algorithms for integrated school bus routing and scheduling problem

International Journal of Cognitive Computing in Engineering, 2021
Bi-objective school bus scheduling optimization problem that is a subset of vehicle fleet scheduling problem is focused in this paper. In the literature, school bus routing and scheduling problem is proven to be an NP-Hard problem.
Eda Koksal, Abhishek R. Hegde, Haresh P. Pandiarajan, Bharadwaj Veeravalli   +3 more
doaj   +1 more source

On the convergence of reinforcement learning [PDF]

Journal of Economic Theory, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +5 more sources