College Information

Subject Detail

Sno Back regulation branch year semester subject_code name credits category
1 Back R23AIML ARTIFICIAL INTELLIGENCE & MACHINE LEARNING (AI&ML) 3 1 23A39502 INTRODUCTION TO REINFORCEMENT LEARNING 3.0 Theory




Syllabus List


Sno subject description note syllabus_file
1 INTRODUCTION TO REINFORCEMENT LEARNING - 23A39502 (Theory) 23A39502

23A39502

Link



Book List


Sno subject title author publisher edition book_type book_file note
1 INTRODUCTION TO REINFORCEMENT LEARNING - 23A39502 (Theory) Reinforcement Learning: An Introduction Richard S. Sutton and Andrew G. Barto MIT Press 2nd Edition 2018 Textbook Link

True

2 INTRODUCTION TO REINFORCEMENT LEARNING - 23A39502 (Theory) An Introduction to Deep Reinforcement Learning François-Lavet et al., Foundations and Trends® in Machine Learning, 2018 None Reference Link

True

3 INTRODUCTION TO REINFORCEMENT LEARNING - 23A39502 (Theory) Foundations of Deep Reinforcement Learning Laura Graesser Wah Loon Keng Pearson None Reference Link

True

4 INTRODUCTION TO REINFORCEMENT LEARNING - 23A39502 (Theory) Reinforcement Learning and Games Aske Plaat NOne None Reference Link

True

5 INTRODUCTION TO REINFORCEMENT LEARNING - 23A39502 (Theory) A Course in Reinforcement Learning 2nd Edition None None 2nd Edition Reference Link

True




OnlineReference List


Sno subject title note




Question Paper List


Sno Subject Question Paper Type Date Title File







Lab List


Sno subject date title