The following is a schedule of the lectures and presentations for CS 4013/5013 Artificial Intelligence for Spring 2019. This schedule will be updated throughout the semester. All readings are from Artificial Intelligence by Russell & Norvig third edition (blue book) unless otherwise noted.
| Date | Topic | Assigned Reading | Assigned | Due |
|---|---|---|---|---|
| Jan 14 (Week 1: Intro and Agent Design) | Introduction to AI | |||
| Jan 16 | Intelligent agents, Search and problem formulation, Agents and environments |
Ch 2 through 2.3, 3.1 | ||
| Jan 21 (Week 2: Problem formulation) | Martin Luther King day - holiday | Project 0: setting up your account | ||
| Jan 23 | Problem formulation, Effective knowledge representations |
3.2-3.3 | ||
| Jan 28 (Week 3: Search) | Uninformed search (BFS, DFS, etc) | 3.4 | Project 1: Reflex agents and knowledge representations | Project 0 |
| Jan 30 | Informed search, Local search, |
3.5 | Homework 1: Problem formulation | |
| Feb 4 (Week 4: Search) | Heuristic search, A* |
3.6 | ||
| Feb 6 | A* | 3.5,3.6 |
|
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| Feb 11 (Week 5: Adversaries) | A*, Constructing admissible heuristics |
|
Project 2: Intelligent search | Project 1 |
| Feb 13 | Project 1 demos, Local search and search in the real world | 4.1-4.5 | Homework 2: Uninformed and informed search | Homework 1 |
| Feb 18 (Week 6: Adversaries) | Adversarial search, Alpha-beta pruning | 5.1-5.2, 5.3 | ||
| Feb 20 | Alpha-beta pruning, Large scale games |
5.4-5.5 |
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| Feb 25 (Week 7:MCTS, Learning) | Advanced topic: Multi-Carlo Tree Search, Upper Confidence Bounds/UCT search | Homework 2 | ||
| Feb 27 | UCT search | Homework 3: Adversarial search and MCTS and CSPs | Project 2 | |
| Mar 4 (Week 8: Learning) | Project 2 demos, UCT, Introduction to learning | |||
| Mar 6 | Introduction to learning, Clustering | 18.1 | ||
| Mar 11 (Week 9: Learning) | Evolutionary Computation/Genetic Algorithms |
4.1.4 |
Project 3: Learning | |
| Mar 13 | Linear regression, logistic regression, generalized linear models | 18.6, 18.8 | Homework 3 | |
| Mar 16-24 | Spring Break! |
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| Mar 25 (Week 10: Learning) | Nearest neighbor, Kernel regression Decision trees |
18.6, 18.8 18.3 |
Homework 4: Learning | |
| Mar 27 | Decision trees
|
18.3 | ||
| Apr 1 (Week 11: CSPs) | Constraint satisfaction problems |
6.1-6.5 | ||
| Apr 3 | Evaluating learning models, Overfitting, Model interpretation |
Project 3 | ||
| Apr 8 (Week 12: Planning) | Project 3 demos, Solving CSPs (and complex optimization) using learning | Homework 5: Trees |
Homework 4 | |
| Apr 10 |
Introduction to logic, Introduction to classical planning, |
Ch 7, 8 |
Project 4: Planning, Multi-agent systems and tying it all together | |
| Apr 15 (Week 13: Multi-agent systems and Planning) | Planning, Forward and backwards search, |
10, 12 | ||
| Apr 17 | Planning and acting in the real-world | 11 | Homework 6: Planning | Homework 5 |
| Apr 22 (Week 14: Multi-agent systems and Planning) | Advanced topics: Generative Adversarial Networks (GANs) | |||
| Apr 24 | Advanced topics: Relational models | |||
| Apr 29 (Week 15: Multi-agent systems and Planning) | Introduction to multi-agent systems |
11.4 | Homework 6 | |
| May 1 (Course wrapup) | Multi-agent systems | Project 4 | ||
| May 6 | Final project demos 4:30-6:30pm |
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