Reinforcement Learning by Narayan Hegde ME, CSA@IISc Google 2 - PowerPoint PPT Presentation

Sep 13, 2022 •757 likes •1.13k views

Reinforcement Learning by Narayan Hegde ME, CSA@IISc Google 2 Summer School 2013 3 Summer School 2013 What is it? 4 What could the mechanisms be, by which based on feedback based on our actions by the environment, we learn to act over

Reinforcement Learning by Narayan Hegde ME, CSA@IISc Google
2 Summer School 2013
3 Summer School 2013
What is it? 4 What could the mechanisms be, by which based on feedback based on our actions by the environment, we learn to act over time. Learning by trial and error to perform sequential decision making Markov Decision Process trial-and-error search and delayed reward - are the two most important distinguishing features Summer School 2013
5 Artificial Intelligence Operation Machine Research Learning Reinforcement Learning Control Psychology Theory Game Theory Summer School 2013
Where do you see this 6  Current and Next Generation Automated Robots  Drive Vehicles  Personal Assistant  Traffic-light control  Games like chess  Why don’t we hard code them? What are the benefits  Where can you apply?  What is the greatest example of reinforcement learning? Summer School 2013
The Video of Goal Keeper 7 Summer School 2013
Take Away Get Motivated Model in Real Life Try Building a mathematical model
9 Summer School 2013
10 Summer School 2013
11 Summer School 2013
12 Summer School 2013
13 Summer School 2013
Example of Robot playing Football 14 Summer School 2013
15 Summer School 2013
16 Summer School 2013
17 Summer School 2013
18 Summer School 2013
What is the algorithm paradigm? Summer School 2013
20 Summer School 2013
21 Summer School 2013
22 Summer School 2013
23 Summer School 2013
Thank you and Questions Summer School 2013
25 Summer School 2013
26 Summer School 2013
27 Summer School 2013
28 Summer School 2013
29 Summer School 2013
30 Summer School 2013
31 Summer School 2013
32 Summer School 2013
33 Summer School 2013
34 Summer School 2013
35 Summer School 2013

Recommend

RL Overview of topics About Reinforcement Learning The Reinforcement Learning Problem

Introduction to Reinforcement Learning RL Overview of topics About Reinforcement Learning The Reinforcement Learning Problem Inside an RL agent Temporal difference learning Many faces of Reinforcement Learning What is

551 views • 35 slides

Reinforcement Learning Reinforcement Learning Reinforcement Learning in a nutshell g Imagine

Reinforcement Learning Reinforcement Learning Reinforcement Learning in a nutshell g Imagine playing a new game whose rules you dont know; after a hundred or so moves your don t know; after a hundred or so moves, your opponent announces, You

511 views • 30 slides

Reinforcement Learning You can think of supervised learning as the teacher providing answers

Reinforcement Learning You can think of supervised learning as the teacher providing answers (the class labels) Reinforcement learning: In reinforcement learning, the agent learns Markov Decision Processes based on a punishment/reward

89 views • 6 slides

Examples of Reinforcement Learning Robocup Soccer Teams Stone & Veloso, Reidmiller et al.

Reinforcement Learning Slides by Rich Sutton Mods by Dan Lizotte Refer to Reinforcement Learning: An Introduction by Sutton and Barto Alpaydin Chapter 16 Up until now we have been Supervised Learning Classifying, mostly

891 views • 31 slides

CS885 Reinforcement Learning Module 2: June 6, 2020 Maximum Entropy Reinforcement Learning

CS885 Reinforcement Learning Module 2: June 6, 2020 Maximum Entropy Reinforcement Learning Haarnoja, Tang et al. (2017) Reinforcement Learning with Deep Energy Based Policies, ICML . Haarnoja, Zhou et al. (2018) Soft Actor-Critic: Off-Policy

683 views • 24 slides

Reinforcement Learning Reinforcement Learning Now that you know a little about Optimal Control

Reinforcement Learning Reinforcement Learning Now that you know a little about Optimal Control Theory, you actually have some knowledge in RL. RL shares the overall goal with OCT: solving for a control policy such that the cumulative cost

610 views • 22 slides

Reinforcement Learning CS 4100: Artificial Intelligence Reinforcement Learning II Still

Reinforcement Learning CS 4100: Artificial Intelligence Reinforcement Learning II Still assume a Marko kov decision process (MDP): A se set o of st states s s S A se set o of a actions ( s (per st state) A A mo model

96 views • 5 slides

R i f R i f Reinforcement Learning III Reinforcement Learning III t L t L i i III III Dec

R i f R i f Reinforcement Learning III Reinforcement Learning III t L t L i i III III Dec 03 2008 1 Large State Spaces h When a problem has a large state space we can not longer represent the U or Q functions as explicit tables explicit

436 views • 18 slides

Reinforcement Learning UMaine COS 470/570 Introduction to AI Why reinforcement learning?

Reinforcement Learning<br/><br/> 4/25/19, 8*06 PM Reinforcement Learning<br/><br/> 4/25/19, 8*06 PM Reinforcement Learning UMaine COS 470/570 Introduction to AI Why reinforcement learning? Spring 2019 Created:

371 views • 15 slides

7. Motor Control and Reinforcement Learning Outline A. Action Selection and Reinforcement B.

7. Motor Control and Reinforcement Learning Outline A. Action Selection and Reinforcement B. Temporal Difference Reinforcement Learning C. PVLV Model D. Cerebellum and Error-driven Learning 2/23/18 COSC 494/594 CCN 2 Sensory-Motor Loop

790 views • 56 slides

Deep Reinforcement Learning [Mastering the Game of Go with Deep Reinforcement Learning and Tree

Deep Reinforcement Learning [Mastering the Game of Go with Deep Reinforcement Learning and Tree Search, Nature 2016] CS 486/686 University of Waterloo Lecture 21: July 12, 2017 Outline AlphaGo Supervised Learning of Policy Networks

541 views • 15 slides

Reinforcement Learning CS 4100: Artificial Intelligence Reinforcement Learning Ja Jan-Wi

Reinforcement Learning CS 4100: Artificial Intelligence Reinforcement Learning Ja Jan-Wi Willem van de Meent Northeastern University [These slides were created by Dan Klein and Pieter Abbeel for CS188 Intro to AI at UC Berkeley. All CS188

145 views • 10 slides

Reinforcement Learning AIMA Chapters: 21.1, 21.2, 21.3. Sutton and Barto, Reinforcement Learning:

Reinforcement Learning Reinforcement Learning AIMA Chapters: 21.1, 21.2, 21.3. Sutton and Barto, Reinforcement Learning: an Introduction, 2nd Edition: Chapters 6 (6.1 6.5) Outline Reinforcement Learning Reinforcement Learning: the

587 views • 27 slides

Module 11 Introduction to Reinforcement Learning CS 886 Sequential Decision Making and

Module 11 Introduction to Reinforcement Learning CS 886 Sequential Decision Making and Reinforcement Learning University of Waterloo Machine Learning Supervised Learning Teacher tells learner what to remember Reinforcement Learning

401 views • 29 slides

1 Pure Reinforcement Learning vs. Reinforcement Learning Monte-Carlo Planning No knowledge

CSE 573: Artificial Intelligence Todo Reinforcement Learning Add simulations from 473 Dan Weld Add UCB bound (cut bolzman & constant epsilon Add snazzy videos (pendulum, zico kolter See http://www See http://www-

462 views • 11 slides

Safe Reinforcement Learning Philip S. Thomas Stanford CS234: Reinforcement Learning, Guest

Safe Reinforcement Learning Philip S. Thomas Stanford CS234: Reinforcement Learning, Guest Lecture May 24, 2017 Lecture overview What makes a reinforcement learning algorithm safe ? Notation Creating a safe reinforcement learning

1.42k views • 88 slides

Reinforcement Learning Framework Reinforcement Learning Rewards, Returns Lectures 4 and 5

1 Reinforcement Learning Framework Reinforcement Learning Rewards, Returns Lectures 4 and 5 Environment Dynamics Gillian Hayes Components of a Problem 18th January 2007 Values and Action Values, V and Q Optimal Policies

109 views • 7 slides

Introduction to Reinforcement Learning Bayesian Methods in Reinforcement Learning ICML 2007

Introduction to Reinforcement Learning Bayesian Methods in Reinforcement Learning ICML 2007 sequential decision making under uncertainty ? How Can I ... ? Move around in the physical world (e.g. driving, navigation) Play and win a game

519 views • 21 slides

Neural Combinatorial Optimization With Reinforcement Learning CS885 Reinforcement Learning Paper

Neural Combinatorial Optimization With Reinforcement Learning CS885 Reinforcement Learning Paper by Bello, I., Pham, H., Le, Q. V., Norouzi, M., & Bengio, S. (2016) Presented by Yan Shi Outline 1. Introduction 2. Background 3. Algorithms

966 views • 27 slides

Todays Outline Reinforcement Learning Dan Weld Reinforcement Learning Q-value

5/7/2012 CSE 473: Artificial Intelligence Todays Outline Reinforcement Learning Dan Weld Reinforcement Learning Q-value iteration Q-learning Exploration / exploitation Linear function approximation Linear function

159 views • 12 slides

CSC2621 Topics in Robotics Reinforcement Learning in Robotics Week 11: Hierarchical Reinforcement

CSC2621 Topics in Robotics Reinforcement Learning in Robotics Week 11: Hierarchical Reinforcement Learning Animesh Garg Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning Richard S. Sutton , Doina

2.18k views • 29 slides

Reinforcement Learning (RL) CE-717: Machine Learning Sharif University of Technology M.

Reinforcement Learning (RL) CE-717: Machine Learning Sharif University of Technology M. Soleymani Fall 2018 Most slides have been taken from Klein and Abdeel, CS188, UC Berkeley. Reinforcement Learning (RL) Learning as a result of

1.45k views • 133 slides

1 Deep Reinforcement Learning Qianqian Li, Nayeon Koong, Langtian He What is deep reinforcement

1 Deep Reinforcement Learning Qianqian Li, Nayeon Koong, Langtian He What is deep reinforcement learning? Agent/Actor + Action + Environment + State + Reward How does reinforcement learning work?

792 views • 31 slides

Machine Learning for NLP Reinforcement learning Aurlie Herbelot 2019 Centre for Mind/Brain

Machine Learning for NLP Reinforcement learning Aurlie Herbelot 2019 Centre for Mind/Brain Sciences University of Trento 1 Introduction 2 Reinforcement learning: intuition Reinforcement learning: like learning to ride a bicycle.

1.18k views • 58 slides