Show overview
The CIS 5210 Podcast has published 8 episodes during 2024. That works out to roughly 2 hours of audio in total. Releases follow a several-times-a-week cadence.
Episodes typically run ten to twenty minutes — most land between 12 min and 15 min — and the run-time is fairly consistent across the catalogue. It is catalogued as a EN-language Education show.
The catalogue appears to be on hiatus or wound down — the most recent episode landed 1.6 years ago, with no new episodes in over a year. Published by Chris Callison-Burch.
From the publisher
This is a podcast for the University of Pennsylvania’s Artificial Intelligence Course (CIS 5210). The episodes are automatically generated using NotebookLM by uploading Prof. Chris Callison-Burch’s lecture notes and lecture slides.
Latest Episodes
Ep 8CIS 5210 - Module 8 - Reinforcement Learning
This episode explores reinforcement learning and its relationship to MDPs. Also mentioned: exploration v. exploitation, multi-arm bandits, model-free learning, q-learning. Disclosure: This episode was generated using NotebookLM by uploading Professor Chris Callison-Burch's lecture notes and slides.
Ep 7CIS 5210 - Module 7 - Markov Decision Processes
This episode explores MDPs, covering stochastic environments, transition functions, reward functions, policies, value iteration, policy iteration, expected utility, finite vs. infinite horizons, discount factors, etc. Disclosure: This episode was generated using NotebookLM by uploading Professor Chris Callison-Burch's lecture notes and slides.
Ep 6CIS 5210 - Module 6 - Knowledge-Based Agents and Logical Reasoning
This episode explores knowledge-based agents in AI, covering knowledge bases, inference, propositional logic, theorem proving, logical equivalence, resolution, conjunctive normal form (CNF), proof by contradiction, and distributed knowledge representation and reasoning. Disclosure: This episode was generated using NotebookLM by uploading Professor Chris Callison-Burch's lecture notes and slides.
Ep 5CIS 5210 - Module 5 - CSPs
This episode explores constraint satisfaction problems (CSPs), covering variables, domains, constraints, backtracking search, heuristics, forward checking, constraint propagation, and arc consistency. Disclosure: This episode was generated using NotebookLM by uploading Professor Chris Callison-Burch's lecture notes and slides.
Ep 4CIS 5210 - Module 4 - Adversarial Search
This episode explores adversarial search in game-playing AI, covering game formulation, minimax, game trees, evaluation functions, alpha-beta pruning and expectimax. Disclosure: This episode was generated using NotebookLM by uploading Professor Chris Callison-Burch's lecture notes and slides.
Ep 3CIS 5210 - Module 3 - Informed Search
This episode explores informed search algorithms in AI, focusing on A* search. Key topics include: Importance of heuristics in guiding searches, and the role of admissible heuristics and in optimal solutions. Disclosure: This episode was generated using NotebookLM by uploading Professor Chris Callison-Burch's lecture notes and slides.
Ep 2CIS 5210 - Module 2 - Uninformed Search
This episode explores uninformed search algorithms like BFS, DFS, and iterative deepening search. Disclosure: This episode was generated using NotebookLM.
Ep 1CIS 5210 - Module 1 - Rational Agents
This episode explores rational agents in AI, covering: Philosophical foundations Historical context Task environments Disclosure: This episode was generated using NotebookLM.