CS885 - Semi-Markov Decision Processes

Explore semi-Markov decision processes in this 36-minute lecture by Pascal Poupart. Delve into reinforcement learning concepts, queueing theory, and Bellman's equation. Learn about the option framework, transition dynamics, and reward functions as they relate to semi-Markov processes. Gain insights into the application of these concepts in decision-making scenarios and understand how they extend traditional Markov decision processes.

Introduction
Reinforcement Learning
SemiMarkov Processes
Queueing Theory
Bellmans Equation
Option Framework
Transition Dynamics
Reward Function
Options
Bellman Equation