The CIS 5210 Podcast

Chris Callison-Burch

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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.

2024. 10. 22.

CIS 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.

15분
2024. 10. 05.

CIS 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.

17분
2024. 09. 29.

CIS 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.

14분
2024. 09. 29.

CIS 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.

11분
2024. 09. 29.

CIS 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.

10분
2024. 09. 28.

CIS 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.

13분
2024. 09. 28.

CIS 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.

13분
2024. 09. 28.

CIS 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.

19분

8개의 에피소드

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.

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Chris Callison-Burch
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2024년
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8
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The CIS 5210 Podcast

The CIS 5210 Podcast

에피소드

CIS 5210 - Module 8 - Reinforcement Learning

CIS 5210 - Module 7 - Markov Decision Processes

CIS 5210 - Module 6 - Knowledge-Based Agents and Logical Reasoning

CIS 5210 - Module 5 - CSPs

CIS 5210 - Module 4 - Adversarial Search

CIS 5210 - Module 3 - Informed Search

CIS 5210 - Module 2 - Uninformed Search

CIS 5210 - Module 1 - Rational Agents

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