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See all on WikipediaReinforcement learning - Wikipedia
Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent ought to take actions in a dynamic environment in order to maximize the cumulative reward. Reinforcement learning is one of three basic machine learning … See more
Due to its generality, reinforcement learning is studied in many disciplines, such as game theory, control theory, operations research See more
Even if the issue of exploration is disregarded and even if the state was observable (assumed hereafter), the problem remains to … See more
The exploration vs. exploitation trade-off has been most thoroughly studied through the multi-armed bandit problem and for finite state space … See more
Both the asymptotic and finite-sample behaviors of most algorithms are well understood. Algorithms with provably good online performance … See more
Associative reinforcement learning
Associative reinforcement learning tasks combine facets of stochastic learning automata tasks and … See moreWikipedia text under CC-BY-SA license Reinforcement learning from human feedback - Wikipedia
WEBIn machine learning, reinforcement learning from human feedback ( RLHF) is a technique to align an intelligent agent to human preferences. It involves training a reward model to …
Deep reinforcement learning - Wikipedia
WEBDeep reinforcement learning ( deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem of a …
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Q-learning - Wikipedia
WEBQ-learning is a model-free reinforcement learning algorithm to learn the value of an action in a particular state. It does not require a model of the environment (hence "model-free"), …
Reinforcement learning - Wikipedia
WEBReinforcement learning ( RL) is an area of machine learning concerned with how software agents ought to take actions in an environment so as to maximize some notion of …
Reinforcement - Wikipedia
WEBIn behavioral psychology, reinforcement refers to consequences that increase the likelihood of an organism's future behavior, typically in the presence of a particular antecedent …
Model-free (reinforcement learning) - Wikipedia
WEBIn reinforcement learning (RL), a model-free algorithm (as opposed to a model-based one) is an algorithm which does not estimate the transition probability distribution (and the …
Reinforcement learning - Simple English Wikipedia, the free …
WEBReinforcement learning (RL) is teaching a software agent how to behave in an environment by telling it how well it's doing. It is an area of machine learning inspired by behaviorist …
Multi-agent reinforcement learning - Wikipedia
WEBMulti-agent reinforcement learning (MARL) is a sub-field of reinforcement learning. It focuses on studying the behavior of multiple learning agents that coexist in a shared …
A Beginner's Guide to Deep Reinforcement Learning
WEBDeep reinforcement learning combines artificial neural networks with a framework of reinforcement learning that helps software agents learn how to reach their goals. That is, it unites function approximation and target …
[2201.12122] Can Wikipedia Help Offline Reinforcement Learning?
WEBIn this paper, we look to take advantage of this formulation of reinforcement learning as sequence modeling and investigate the transferability of pre-trained sequence models …
强化学习 - 维基百科，自由的百科全书
WEB强化学习 （英語： Reinforcement learning ，簡稱 RL ）是 机器学习 中的一个领域，强调如何基于 环境 而行动，以取得最大化的预期利益 [1] 。. 强化学习是除了 监督学习 和 …
What Is Reinforcement Learning? - H2O
WEBReinforcement learning (RL) is a subfield of machine learning that enables AI-based systems to execute actions through trial and error. RL can optimize collective rewards …
強化学習 - Wikipedia
WEB強化学習 （きょうかがくしゅう、 英: reinforcement learning 、 RL ）は、ある環境内における 知的エージェント が、現在の状態を観測し、得られる収益（累積報酬）を最大 …
The History of Reinforcement Learning - The Research Scientist …
WEBReinforcement learning has an extensive history with a fascinating cross-pollination of ideas, generating research that sent waves through behavioural science, cognitive …
What is Reinforcement Learning From Human Feedback (RLHF)
WEBReinforcement Learning From Human Feedback (RLHF) is an advanced approach to training AI systems that combines reinforcement learning with human feedback. It is a …
Reinforcement learning - GeeksforGeeks
WEBReinforcement learning is an autonomous, self-teaching system that essentially learns by trial and error. It performs actions with the aim of maximizing rewards, or in other words, …
WEBOur findings allude to the potential impact of large scale pre-training for reinforcement learning, given its surprising efficacy when transferring from a distant sequence …
Reinforcement Learning Definitions | Pathmind
WEBReinforcement learning happens to codify the structure of a human life in mathematical statements, and as you sink deeper into RL, you will add a layer of mathematical terms …
Category : Reinforcement learning - Wikimedia
WEBMedia in category "Reinforcement learning". The following 20 files are in this category, out of 20 total. A-novel-approach-to-locomotion-learning-Actor-Critic-architecture-using …
What is reinforcement learning? | Definition from TechTarget
WEBReinforcement learning (RL) is a machine learning training method that trains software to make certain desired actions. Reinforcement learning is based on rewarding desired …
Reinforcement learning - Computer Science Wiki
WEBReinforcement learning is a type of machine learning algorithm that allows an agent to learn by interacting with its environment and receiving feedback in the form of rewards or …
WEBal networks, deep learning, and other machine learning techniques. Although reinforcement learning has been primarily used in video games, recent advancements …
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