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This schedule is tentative and subject to change. It may be a bit ambitious.

Supplmentary and optional background reading provided when appropriate.

R&N == Aritificial Intelligence: A Modern Approach, Russell and Norvig, 3rd edition.

References for Unit 1 (Logic)

For the unit on logic you may also want to consult:

  • Category Theory for the Sciences, Spivak, pdf
  • Logic in Computer Science, Huth and Ryan
  • Logic for Computer Scientists, Schoening

Huth and Ryan is an excellent introductory text for temporal and epistemic logics, which we will touch on in Unit 3 (agent-based reasoning).

References for Unit 3 (Agents and Probabilistic State)

  • Advanced Data Analysis from an Elementary Point of View, Part III, Shalizi, pdf
  • Logic in Computer Science, Huth and Ryan

References for Unit 4 (Time and Programs)

Date Topic Form Deadlines & Notes
Wed, Jan 19 Intro: What is AI? Lecture
Fri, Jan 21 Knowledge Representation Lecture R&N: 12.1, 12.2
Set notation cheatsheet
NSF Workshop: Research Challenges and Opportunitites in KR
Mon, Jan 24 Propositional Logic Lecture Add Deadline
R&N: 7.3
Wed, Jan 26 First Order (Predicate) Logic Lecture Theory Assignment 1 out
R&N 8.2
Fri, Jan 28 Logical Inference I Lecture R&N 7.5
Mon, Jan 31 Review of Logical Inference Michael Q&A No Teams broadcast today
Programming Assignment 1 out
Wed, Feb 2 Logical Inference II and Resolution Videos Theory Assignment 1 due (soft)
R&N 7.5, 9.5
Fri, Feb 4 Application: Law and Logic Programming Lecture Drop Deadline
Theory Assignment 1 due (hard)
R&N 9.4
Mon, Feb 7 Proofs as Planning and Intro to Search Lecture R&N 10.1, 10.2
Wed, Feb 9 Exam 1: Logic Exam
Fri, Feb 11 Background: Discrete Probability Theory Lecture Programming Assignment 1 due (soft)
Fri, Feb 18 Search Agents Lecture (Michael) R&N 2.1-4
Mon, Feb 21 President's Day No Class
Wed, Feb 23 Uninformed Search Lecture (Michael) R&N 3.1-4
Fri, Feb 25 In-Class Activity: Search Lecture (Michael)
Mon, Feb 28 A* and Adversarial Search Lecture (Michael) R&N 3.5-6, 5.1-3
Wed, Mar 2 Constraint Satisfaction Problems Lecture (Michael) R&N 6.1-5
Fri, Mar 4 In-Class Actibity: CSP Lecture (Michael)
Mon, Mar 7 Spring Recess No Class
Wed, Mar 9 Spring Recess No Class
Fri, Mar 11 Spring Recess No Class
Mon, Mar 14 AI Security Topics Lecture (Michael)
Wed, Mar 16 Uncertainty in States Lecture R&N 12.1-4
Fri, Mar 18 Queries and Partial Observability Lecture R&N 13.1-2
We briefly discussed what a naive causal structure learning algorithm would look like. For a full treatment of constraint-based causal structure learning, see Shalizi Ch. 25
Mon, Mar 21 Causal Graphical Models Lecture Notebook exercises
Actual notebook
Wed, Mar 23 Modal Logics for Knowledge and Belief Lecture Modal Logic Playground
DSL for belief programming with partial observability
Fri, Mar 25 Representing agent knowledge with \(KT45^n\) Lecture An Introduction to Logics of Knowledge and Belief ICAPS 2020 Tutorial on Epistemic Planning
Mon, Mar 28 Elementary Decision Theory Lecture Blog post
Wed, Mar 30 Elementary Game Theory Lecture R&N 17.5, 17.6
Epistemic Game Theory
Two-person Zero-sum Games Note that in this document, Player 1 chooses a row, whereas our Player 1 chooses a column
Fri, Apr 1 Summary: Acting under incomplete or uncertain knowledge Lecture Probabilistic Modal Logic
Factored Models for Probabilistic Modal Logic
Mon, Apr 4 Temporal Logic for Representing Transitions Lecture Last day to Withdraw
R&N 14, 17
Wed, Apr 6 Exam Review Review
Fri, Apr 8 Exam 3: Agent-based Reasoning Exam
Mon, Apr 11 Exam 3: Agent-based Reasoning Make-Up Exam
Wed, Apr 13 Probabilistic Modeling Review In-class Work Probabilistic Modeling Worksheet out
Fri, Apr 15 Exam and programming assignment review In-class Unit 3 review Programming Assignment 2 out
Mon, Apr 18 LTL Applications Lecture
Wed, Apr 20 Markov Chains for Representing Transitions Lecture
Fri, Apr 22 Properties of Markov Chains and MDPs Lecture Probabilistic Modeling worksheet due in class
Irreducibility and Aperiodicity Demo
Mon, Apr 25 HMMs, MDPs, Intro to RL Lecture Probabilistic Modeling worksheet solutions out
Real Applications of MDPs
Wed, Apr 27 Lecture
Fri, Apr 29 Lecture Programming Assignment 2 due
Programming Assignment 3 out
Mon, May 2 Lecture VerifAI: A Toolkit for the Formal Design and Analysis of Artificial Intelligence-Based Systems
Wed, May 4 Exam Review Review
Fri, May 6 Exam 4: Time and Programs Exam Last Day of Classes
Thu, May 12 Final Exam 7:30am-10:15, VOTEY 207 All programming assignments due (hard)