Modules / Lectures


Sl.No Chapter Name MP4 Download
1Tutorial 1 - Probability Basics 1Download
2Tutorial 1-Probability basics2Download
3Tutorial 2-Linear algebra-1Download
4Tutorial 2-Linear algebra-2Download
5Introduction to RLDownload
6RL Framework and applicationsDownload
7Introduction to Immediate RLDownload
8Bandit OptimalitiesDownload
9Value function based methodsDownload
10UCB 1Download
11Concentration BoundsDownload
12UCB 1 TheoremDownload
13PAC BoundsDownload
14Median EliminationDownload
15Thompson SamplingDownload
16Policy SearchDownload
17REINFORCEDownload
18Contextual BanditsDownload
19Full RL IntroductionDownload
20Returns, Value Functions and MDPsDownload
21MDP ModellingDownload
22Bellman EquationDownload
23Bellman Optimality EquationDownload
24Cauchy Sequence and Green's EquationDownload
25Banach Fixed Point TheoremDownload
26Convergence ProofDownload
27Lpi ConvergenceDownload
28Value IterationDownload
29Policy IterationDownload
30Dynamic ProgrammingDownload
31Monte CarloDownload
32Control in Monte CarloDownload
33Off Policy MCDownload
34UCTDownload
35TD(0)Download
36TD(0) ControlDownload
37Q-LearningDownload
38AfterstateDownload
39Eligibility TracesDownload
40Backward View of Eligibility TracesDownload
41Eligibility Trace ControlDownload
42Thompson Sampling RecapDownload
43Function ApproximationDownload
44Linear ParameterizationDownload
45State Aggregation MethodsDownload
46Function Approximation and Eligibility TracesDownload
47LSTD and LSTDQDownload
48LSPI and Fitted QDownload
49DQN and Fitted Q-IterationDownload
50Policy Gradient ApproachDownload
51Actor Critic and REINFORCEDownload
52REINFORCE (cont'd)Download
53Policy Gradient with Function ApproximationDownload
54Hierarchical Reinforcement LearningDownload
55Types of OptimalityDownload
56Semi Markov Decision ProcessesDownload
57OptionsDownload
58Learning with OptionsDownload
59Hierarchical Abstract MachinesDownload
60MAXQDownload
61MAXQ Value Function DecompositionDownload
62Option DiscoveryDownload
63POMDP IntroductionDownload
64Solving POMDPDownload

Sl.No Chapter Name English
1Tutorial 1 - Probability Basics 1Download
Verified
2Tutorial 1-Probability basics2Download
Verified
3Tutorial 2-Linear algebra-1Download
Verified
4Tutorial 2-Linear algebra-2Download
Verified
5Introduction to RLDownload
Verified
6RL Framework and applicationsDownload
Verified
7Introduction to Immediate RLDownload
Verified
8Bandit OptimalitiesDownload
Verified
9Value function based methodsDownload
Verified
10UCB 1Download
Verified
11Concentration BoundsDownload
Verified
12UCB 1 TheoremDownload
Verified
13PAC BoundsDownload
Verified
14Median EliminationDownload
Verified
15Thompson SamplingDownload
Verified
16Policy SearchDownload
Verified
17REINFORCEDownload
Verified
18Contextual BanditsDownload
Verified
19Full RL IntroductionDownload
Verified
20Returns, Value Functions and MDPsDownload
Verified
21MDP ModellingDownload
Verified
22Bellman EquationDownload
To be verified
23Bellman Optimality EquationDownload
Verified
24Cauchy Sequence and Green's EquationDownload
Verified
25Banach Fixed Point TheoremDownload
Verified
26Convergence ProofDownload
Verified
27Lpi ConvergenceDownload
Verified
28Value IterationDownload
Verified
29Policy IterationDownload
Verified
30Dynamic ProgrammingDownload
Verified
31Monte CarloDownload
Verified
32Control in Monte CarloDownload
Verified
33Off Policy MCDownload
Verified
34UCTDownload
Verified
35TD(0)Download
Verified
36TD(0) ControlDownload
Verified
37Q-LearningDownload
Verified
38AfterstateDownload
Verified
39Eligibility TracesDownload
Verified
40Backward View of Eligibility TracesDownload
Verified
41Eligibility Trace ControlDownload
To be verified
42Thompson Sampling RecapDownload
To be verified
43Function ApproximationDownload
To be verified
44Linear ParameterizationDownload
To be verified
45State Aggregation MethodsDownload
To be verified
46Function Approximation and Eligibility TracesDownload
To be verified
47LSTD and LSTDQDownload
To be verified
48LSPI and Fitted QDownload
To be verified
49DQN and Fitted Q-IterationDownload
To be verified
50Policy Gradient ApproachDownload
To be verified
51Actor Critic and REINFORCEDownload
To be verified
52REINFORCE (cont'd)Download
To be verified
53Policy Gradient with Function ApproximationDownload
To be verified
54Hierarchical Reinforcement LearningDownload
Verified
55Types of OptimalityDownload
Verified
56Semi Markov Decision ProcessesDownload
Verified
57OptionsDownload
Verified
58Learning with OptionsDownload
Verified
59Hierarchical Abstract MachinesDownload
Verified
60MAXQDownload
To be verified
61MAXQ Value Function DecompositionDownload
To be verified
62Option DiscoveryDownload
To be verified
63POMDP IntroductionDownload
To be verified
64Solving POMDPDownload
To be verified


Sl.No Language Book link
1EnglishNot Available
2BengaliNot Available
3GujaratiNot Available
4HindiNot Available
5KannadaNot Available
6MalayalamNot Available
7MarathiNot Available
8TamilNot Available
9TeluguNot Available