關於 reinforcement learning ，我們在網路上蒐集到這些相關的討論、資訊與評價

#11. Reinforcement Learning Tutorial - Javatpoint

Reinforcement Learning is a feedback-based Machine learning technique in which an agent learns to behave in an environment by performing the actions and seeing ...

#12. [Day-28] 增強式學習(Reinforcement learning) 介紹

自從Alpha Go擊敗人類後開始，大家開始重視增強式學習演算法的能力，沒想到能透過一個Deep learning 、 Machine learning的演算法，能擊敗最強的圍棋手。有興趣的話Netflix ...

#13. The Beginner's Guide to Deep Reinforcement Learning [2021]

Reinforcement Learning is a type of machine learning algorithm that learns to solve a multi-level problem by trial and error. The machine is ...

#14. Sutton & Barto Book: Reinforcement Learning: An Introduction

Reinforcement Learning : An Introduction. Small book cover. Richard S. Sutton and Andrew G. Barto. Second Edition (see here for the first edition)

#15. CS234: Reinforcement Learning Winter 2021 - Stanford ...

Course Description & Logistics. To realize the dreams and impact of AI requires autonomous systems that learn to make good decisions. Reinforcement learning is ...

#16. Reinforcement learning - Scholarpedia

An RL agent learns from the consequences of its actions, rather than from being explicitly taught and it selects its actions on basis of its ...

#17. Reinforcement Learning for Decision-Making and Control in ...

Reinforcement Learning for Decision-Making and Control in Power Systems: Tutorial, Review, and Vision. Authors:Xin Chen, Guannan Qu, Yujie Tang, Steven Low, Na ...

#18. Reinforcement Learning - Microsoft Research

Reinforcement learning is the study of decision making over time with consequences. The field has developed systems to make decisions in complex ...

#19. Deep Reinforcement Learning in Action - Manning Publications

Deep reinforcement learning AI systems rapidly adapt to new environments, a vast improvement over standard neural networks. A DRL agent learns like people do, ...

#20. Demystifying deep reinforcement learning | VentureBeat

Basically, the goal of reinforcement learning is to map states to actions in a way that maximizes rewards. But what exactly does the RL agent ...

#21. Use Reinforcement Learning with Amazon SageMaker

Reinforcement learning (RL) combines fields such as computer science, neuroscience, and psychology to determine how to map situations to actions to maximize ...

#22. Artificial Intelligence: What Is Reinforcement Learning

At the core of reinforcement learning is the concept that the optimal behaviour or action is reinforced by a positive reward. Similar to toddlers learning how ...

#23. What Is Reinforcement Learning? - MATLAB & Simulink

Reinforcement learning is a type of machine learning technique where a computer agent learns to perform a task through repeated trial and error interactions ...

#24. 10 Real-Life Applications of Reinforcement Learning

In Reinforcement Learning (RL), agents are trained on a reward and punishment mechanism. The agent is rewarded for correct moves and ...

#25. ShangtongZhang/reinforcement-learning-an-introduction

Python Implementation of Reinforcement Learning: An Introduction - GitHub - ShangtongZhang/reinforcement-learning-an-introduction: Python Implementation of ...

#26. Evolving Reinforcement Learning Algorithms - Google AI Blog

A long-term, overarching goal of research into reinforcement learning (RL) is to design a single general purpose learning algorithm that can ...

#27. Comparing Deep Reinforcement Learning Algorithms' Ability ...

Reinforcement Learning (RL) controllers have proved to effectively tackle the dual objectives of path following and collision avoidance.

#28. RLlib: Scalable Reinforcement Learning — Ray v1.8.0

RLlib is an open-source library for reinforcement learning that offers both high scalability and a unified API for a variety of applications. RLlib natively ...

#29. 强化学习(Reinforcement Learning) | 莫烦Python

强化学习Reinforcement Learning 是机器学习大家族中重要一员. 他的学习方式就如一个小baby. 从对身边的环境陌生, 通过不断与环境接触, 从环境中学习规律, ...

#30. Reinforcement Learning - Reddit

r/reinforcementlearning: Reinforcement learning is a subfield of AI/statistics focused on exploring/understanding complicated environments and …

#31. Artificial Intelligence: Reinforcement Learning in Python | Udemy

Reinforcement learning has recently become popular for doing all of that and more. Much like deep learning, a lot of the theory was discovered in the 70s and ...

#32. Deep Reinforcement Learning Online Course - Udacity

Learn the deep reinforcement learning skills that are powering amazing advances in AI & start applying these to applications. Learn online with Udacity.

#33. Introduction to RL and Deep Q Networks | TensorFlow Agents

Reinforcement learning (RL) is a general framework where agents learn to perform actions in an environment so as to maximize a reward.

#34. Reinforcement Learning - Keras

Code examples / Reinforcement Learning. Reinforcement Learning. Actor Critic Method · Deep Deterministic Policy Gradient (DDPG) · Deep Q-Learning for Atari ...

#35. Reinforcement Learning | SpringerLink

Reinforcement learning algorithms seek to learn a policy (mapping from states to actions) that maximize the reward received over time. Unlike in supervised ...

#36. Reinforcement Learning - an overview | ScienceDirect Topics

Reinforcement learning is a framework for finding the best policy that specifies how you act next and that maximizes the total reward you will receive. You do ...

#37. Reinforcement Learning, Second Edition | The MIT Press

Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to ...

#38. Robustly Learning Composable Options in Deep ... - IJCAI

Hierarchical reinforcement learning (HRL) is only effective for long-horizon problems when high-level skills can be reliably sequentially executed.

#39. Reinforcement Learning Foundations Online Class - LinkedIn

Learn the basics of reinforcement learning (RL), including the terminology, the kinds of problems you can solve with RL, and the different methods for ...

#40. 第16講Reinforcement Learning/Q-learning - 清華大學開放式課程

Introduction · Markov Decision Process (MDP) · Value Iteration · Policy Iteration · Reinforcement Learning · Model-Free RL based on MC Estimation.

#41. Reinforcement Learning | Computing Science - University of ...

Reinforcement learning is a body of theory and algorithms for optimal decision making developed within the machine learning and operations research ...

#42. Reinforcement Learning [Book] - O'Reilly Media

Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to ...

#43. An introduction to Q-Learning: Reinforcement Learning

Learn about the basic concepts of reinforcement learning and implement a simple RL algorithm called Q-Learning.

#44. Efficient and targeted COVID-19 border testing via ... - Nature

1: A reinforcement learning system for COVID-19 testing (Eva). figure1. Arriving passengers submit travel and demographic information 24 h ...

#45. Reinforcement Learning (DQN) Tutorial - PyTorch

Reinforcement Learning (DQN) Tutorial. Author: Adam Paszke. This tutorial shows how to use PyTorch to train a Deep Q Learning (DQN) agent on the CartPole-v0 ...

#46. Reinforcement Learning — The Third Paradigm of Machine ...

Reinforcement learning is a semi-supervised method of making a machine interact with the environment similar to a human to automatically ...

#47. Reinforcement learning – 3A | ENSAE Paris

Reinforcement learning : Taming the Bandit. Moez DRAIEF (former associate professor of statistical learning at Imperial College 2007- 2016 and assistant ...

#48. A 24x Speedup for Reinforcement Learning with RLlib + Ray

Author: Raoul Khouri (Two Sigma). Presented at: Ray Summit 2021. Abstract: Training a reinforcement learning (RL) agent is compute intensive.

#49. Deep Reinforcement Learning | PNNL

Other forms of reinforcement learning are also gaining steam, including inverse reinforcement learning, in which a machine learns from observing an expert.

#50. What is Reinforcement Learning | IGI Global

What is Reinforcement Learning? Definition of Reinforcement Learning: a type of machine learning in which an agent learns, through its own experience, ...

#51. CS 7642: Reinforcement Learning - Georgia Tech OMSCS

Topics include Markov decision processes, stochastic and repeated games, partially observable Markov decision processes, and reinforcement learning.

#52. A Distributional Perspective on Reinforcement Learning

By con- trast, we believe the value distribution has a central role to play in reinforcement learning. Contraction of the policy evaluation Bellman operator.

#53. Algorithms for Reinforcement Learning - Morgan & Claypool ...

Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a ...

#54. Reinforcement learning by Hebbian synapses with adaptive ...

A central problem in learning theory is how the vertebrate brain processes reinforcing stimuli in order to master complex sensorimotor tasks.

#55. Reinforcement Learning: What it is, how it works, benefits ...

Reward rules are determined in the reinforcement learning algorithms. The agent of the model tries to reach maximum rewards by its actions. The ...

#56. A (Long) Peek into Reinforcement Learning - Lil'Log

What is Reinforcement Learning? Key Concepts; Markov Decision Processes; Bellman Equations. Common Approaches. Dynamic Programming; Monte-Carlo ...

#57. A Deep Dive into Reinforcement Learning - Toptal

Reinforcement learning is a biologically inspired trial-and-error method of training an agent. We reward the agent for good actions to reinforce the desired ...

#58. Reinforcement Learning: What is, Algorithms, Applications ...

Reinforcement Learning is defined as a Machine Learning method that is concerned with how software agents should take actions in an environment.

#59. Machine Learning Glossary: Reinforcement Learning - Google ...

reinforcement learning (RL) ... A family of algorithms that learn an optimal policy, whose goal is to maximize return when interacting with an ...

#60. Reinforcement Learning - C3 AI

Reinforcement Learning uses the assignment of scores to action steps to maximize the total reward captured from a sequence of decisions.

#61. Reinforcement Learning: A Survey - Journal of Artificial ...

Reinforcement learning is the problem faced by an agent that learns behavior through trial-and-error interactions with a dynamic environment. The work described ...

#62. Theory of Reinforcement Learning - Simons Institute

This program aims to advance the theoretical foundations of reinforcement learning (RL) and foster new collaborations between researchers across RL and ...

#63. A Comprehensive Guide to Reinforcement Learning

Reinforcement learning is an area of ML concerned with how agents ought to take actions in an environment to maximize the notion of reward.

#64. Reinforcement Learning: How Machines Learn From Their ...

Reinforcement learning (RL) is a machine learning technique that focuses on how AI agents should take actions in an environment to maximize ...

#65. The Fundamentals of Reinforcement Learning and ... - Cnvrg.io

In general, Reinforcement Learning is used when there is the need to balance the delayed benefit with situational decision-making. So, Reinforcement Learning ...

#66. What is Reinforcement Learning (RL)? - Techopedia

A reinforcement learning algorithm, which may also be referred to as an agent, learns by interacting with its environment.

#67. Reinforcement Learning in R - CRAN

2020-03-02. This vignette gives an introduction to the ReinforcementLearning package, which allows one to perform model-free reinforcement in R. The ...

#68. What Happened in Reinforcement Learning in 2021

What makes reinforcement learning (RL) different from other kinds of algorithms is that it does not depend on historical data sets.

#69. What is Reinforcement Learning? - Unite.AI

Put simply, reinforcement learning is a machine learning technique that involves training an artificial intelligence agent through the ...

#70. A Survey of Preference-Based Reinforcement Learning Methods

Abstract. Reinforcement learning (RL) techniques optimize the accumulated long-term reward of a suitably chosen reward function. However, designing such a ...

#71. EC 700 A3, Spring 2021: Introduction to Reinforcement Learning

Course Description: Reinforcement learning is a subfield of artificial intelligence which deals with learning from repeated interactions with an environment.

#72. 7 Challenges In Reinforcement Learning | Built In

“You have a reinforcement learning problem when the data that you want to learn on is created by the solution,” said John Langford, principal ...

#73. Train an Agent in a Reinforcement Learning Environment

Train an Agent in a Reinforcement Learning Environment ... its reward in the "Simulated Cart Pole" environment using the REINFORCE method (Williams, 1992).

#74. Reinforcement Learning - Goal Oriented Intelligence

This series is all about reinforcement learning (RL)! Here, we'll gain an understanding of the intuition, the math, and the coding involved with RL.

#75. Reinforcement Learning Based Multi-Agent Resilient Control

Reinforcement Learning Based Multi-Agent Resilient Control: From Deep Neural Networks to an Adaptive Law. Authors. Jian Hou Zhejiang Sci-Tech ...

#76. Deep Reinforcement Learning Explained - Jordi TORRES.AI

This is a relaxed introductory series with a practical approach that tries to cover the basic concepts in Reinforcement Learning and Deep ...

#77. Reinforcement learning for bluff body active flow control in ...

Reinforcement learning (RL) has been applied effectively in games and robotic manipulation. We demonstrate the effectiveness of RL in ...

#78. Charting a business course for reinforcement learning

Unlike other types of machine learning, reinforcement learning uses algorithms (which often train AI agents or bots) that typically do not rely ...

#79. Playing Atari with Deep Reinforcement Learning - University ...

Another issue is that most deep learning algorithms assume the data samples to be independent, while in reinforcement learning one typically encounters ...

#80. Reinforcement Learning - Devopedia

Reinforcement learning is the problem faced by an agent that must learn behaviour through trial-and-error interactions with a dynamic ...

#81. Collaborative Evolutionary Reinforcement Learning (CERL)

Reinforcement learning involves training a neural network, often called a policy network, to map observations in the environment to a set of actions at every ...

#82. Deep Learning in a Nutshell: Reinforcement Learning

Reinforcement learning is about positive and negative rewards (punishment or pain) and learning to choose the actions which yield the best ...

#83. Deep Reinforcement Learning: How It Works and Real World ...

Reinforcement Learning (RL) is a concept inspired by behavioral psychology (Sutton, 1984) to use a formal framework to solve decision-making ...

#84. Evolving Reinforcement Learning Algorithms | OpenReview

We propose a method for meta-learning reinforcement learning algorithms by searching over the space of computational graphs which compute the loss function ...

#85. Reinforcement Learning, Fast and Slow - Cell Press

One reservation has been that deep reinforcement learning procedures demand large amounts of training data, suggesting that these algorithms may ...

#86. Reinforcement Learning with Neural Network - Baeldung

Before we begin, let's try to understand what we mean by reinforcement learning and neural networks. 2.1. Machine Learning and Reinforcement ...

#87. What You Need to Know About Deep Reinforcement Learning

Reinforcement learning aims to enable a software/hardware agent to mimic this human behavior through well-defined, well-designed computing ...

#88. Deep Reinforcement Learning: A Brief Survey - IEEE Xplore

Deep reinforcement learning (DRL) is poised to revolutionize the field of artificial intelligence (AI) and represents a step toward building ...

#89. Reinforcement Learning - inwinSTACK | Technical Blog

Reinforcement learning is learning what to do—how to map situations to actions—so as to maximize a numerical reward signal. The learner is not ...

#90. What is Reinforcement Learning? - Global Tech Council

Reinforcement Learning is a machine learning method that addresses how software agents should take actions in an environment.

#91. Artificial Intelligence: What Is Reinforcement Learning - A Simple

At the core of reinforcement learning is the concept that the optimal behavior or action is reinforced by a positive reward. Similar to toddlers ...

#92. Reinforcement Learning Applications - Perfectial

Reinforcement learning solves a different kind of problem. In RL, there's an agent that interacts with a certain environment, thus changing its state, and ...

#93. Reinforcement learning – Part 2: Getting started with Deep Q ...

In the last part of this reinforcement learning series, we had an agent learn Gym's taxi-environment with the Q-learning algorithm.