We develop a unified view of reinforcement learning methods that require a model of the environment, such as dynamic programming and heuristic search, ...

Assignment 2 - Q-Learning and Expected SarsaWelcome to Course 2 Programming Assignment 2. In this notebook, you will: Implement Q-Learning with $\eps ...

Assignment: Policy Evaluation in Cliff Walking EnvironmentWelcome to the Course 2 Module 2 Programming Assignment! In this assignment, you will implem ...

Assignment 4: Chatbot Welcome to the last assignment of Course 4. Before you get started, we want to congratulate you on getting here. It is your 16t ...

Assignment 3: Question AnsweringWelcome to this week’s assignment of course 4. In this you will explore question answering. You will implement the “Te ...

Assignment 2: Transformer SummarizerWelcome to the second assignment of course 4. In this assignment you will explore summarization using the transfor ...

转载自: https://github.com/zht007/tensorflow-practice/blob/master/7_Renforcement_Learning_blackjack/强化学习——MC(蒙特卡洛)玩21点扑克游戏.md 1. 关于21点游戏1.1 规则简介21点的游戏规则详 ...

The key idea of DP, and of reinforcement learning generally, is the use of value functions to organize and structure the search for good policies. As ...

Assignment 2: Optimal Policies with Dynamic ProgrammingWelcome to Assignment 2. This notebook will help you understand: Policy Evaluation and Policy ...

Lesson 1: Policies and Value FunctionsRecognize that a policy is a distribution over actions for each possible state.a policy is a mapping from states ...