Course: PSU CS 441/541 - Artificial Intelligence (Fall 2020) | psu-cs

Weekly outline

General

Collapse all Expand all
Week 1: Intro AI
Lecture: What is AI?
Lecture: Heuristic AI
Readings: Textbook chs. 1-2
Week 2: Single-Agent Search
Lecture: Complete search
Lecture: Advanced search
Readings: Textbook chs. 3-4
Week 3: Applied Search
Lecture: Local Search; CSPs
Lecture: Scheduling and planning
Readings: Textbook chs. 10.1-2, 11.1, 5
Week 4: Adversaries, Logic and AI
Lecture: Adversary search
Lecture: Logic: representation and inference
Reading: Textbook chs. 9, 12 (and review chs. 7-8)
Week 5: Probability and Decision Theory
Lecture: Probability
Lecture: Decisions and Expert Systems
Readings: Textbook chs. 13, 16
Week 6: Machine Learning
Lecture: Naïve Bayesian Reasoning; Machine Learning
Lecture: Machine Learning Methods; Machine Learning Issues
Readings: Textbook ch. 18 (18.5, 18.9 optional)
Week 7: Neural Nets
Lecture: Artificial Neural Nets
Reading: Textbook ch. 18.7
- Neural Nets Page
- Derivation of Backpropagation File
Week 8: Learning and Coordinating
Lecture: Genetic Algorithms
Lecture: Ensembles
Reading: Textbook ch. 4.1.4, 18.10
Week 9: Applications
Thursday 26 November — Thanksgiving, no class meeting
Lecture: Navigation, Control and Robotics
Programming, Minichess, gathering ML data
Reading: ch. 15.1-15.2.1
Week 10: Wrapping Up
Lecture: Adversary Search and Retrograde Analysis
Lecture: AI and Big Neural Nets; AI Ethics