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COL777

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COL777
Deep Reinforcement Learning
Credits 4
Structure 3-0-2
Pre-requisites Any one of COL333 / COL774 / ELL784 /
Overlaps AIL722, ELL729

COL777 : Deep Reinforcement Learning

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COL333/COL671 Introduction and Basics of RL, Markov Decision Processes (MDPs), Dynamic Programming, Monte Carlo Methods (Prediction), Temporal difference Methods (Prediction), Monte Carlo, TD Method (Control), N-step TD, Eligibility Traces, Model based RL, (Action-)Value Function Approximation, Value Function Approximation, Policy Gradient, Policy Gradient, Recent Applications, Misc./Advanced Topics. COL778 principles of Autonomous Systems Credits: 4 (3-0-2) ELL409 Intelligent Agent/Robot Representation. Software and simulation tools. Classical Planning. Anytime and incremental search. Decision-making under Uncertainty. Reinforcement Learning. Imitation learning. State Estimation using Bayesian Networks. Particle Filtering. World Representations. Map representations. Exploration and coverage. Interaction and Intent Inference. Execution and monitoring. Advanced epics and case study. Programming Assignments. Courses of Study 2024-2025 Computer Science and Engineering 166