CSSE 413: Schedule

This schedule is subject to change.

Assignments are listed by their due date.

WeekDatesDay and TopicsAssignments
0 Sep. 2-3 Day 1: Introduction to course
Intelligence: What is it, where do we find it?
Day 2: Constraint Satisfaction
Backtracking search
1 Sep. 6-10 Day 3: Intelligence: How do we test it?
AI landscape, future directions of AI
Sep. 6, BC:
Day 4: Uninformed search Sep. 7, 23:59: Constraint Satisfaction/
Sudoku
assignment
Day 5: Heuristic search, Properties of heuristic functions
Day 6: Deep blue discussion, brute force solutions, EI, pattern matching in chess Sep. 10, BC: Deep Blue summary
2 Sep. 13-17 Day 7: Monte Carlo Tree Search
Planning and problem solving in AI
Day 8: Architectures of modern AI systems: Watson Sep. 14, 23:59: Search/Planning assignment
Day 9: Human robot collaboration
AI HRC project
Context
Day 10: Introduction to NLP
Introduction to HRC assignment
3 Sep. 20-24 Day 11: NLP
Architectures of modern AI systems: Stanford NLP kit
Sep. 20, BC: Cutting-edge work proposal
Day 12: Introduction to Neural Networks
Perceptron
Day 13: Feed-forward neural networks
Backpropagation
Nettalk
Sep. 23, 23:59: Set-up of HRC project and
rudimentary NLP
assignment
Day 14: 5pm: UnifyID
4 Sep. 27-
Oct.1
Day 15: Convolutional neural network and their applications
Day 16: RNNs/LSTMs and their applications
Day 17: Architectures of modern AI systems: AlphaGo
Pattern matching
Day18: Ethics in AI Oct. 1, BC: Who should stop unethical AI? summary
5 Oct. 4-8 Day 19: Inference
Propositional Logic
Day 20: Predicate Logic
Natural logic
Oct. 5, 23:59: Dialog based cleaning robot assignment
Day 21: Symbol based knowledge representation:
logic, frames, semantic nets
Day 22: Presentation of cutting-edge work Presentation slides and responses
6 Oct. 11-12 Day 23: Symbol based knowledge representation: scripts and rules
Expert systems
Day 24: Presentation of cutting-edge work Presentation slides and responses
7 Oct. 18-22 Day 25: Case-based reasoning
Day 26: Analogy
Common sense knowledge and reasoning
Wed. Oct. 20, 23:59: Remembering and Analogy assignment.
Day 27: Strong vs. weak AI
Day 28: Presentation of cutting-edge work Presentation slides and responses
8 Oct. 25-29 Day 29: Introduction to reinforcement learning
Value Iteration
Day 30: Policy Iteration
Markov Decision Processes
Day 31: Q-learning
Day 32: Presentation of cutting-edge work Presentation slides and responses
Oct. 31, 23:59: Sentiment Analysis NN assignment
9 Nov. 1-5 Day 33: Human-robot interaction
AI and Ethics
BC: AI Ethics essay
Day 34: Genetic Algorithms
Day 35: Multi-agent planning
AI and the Future of Work
Nov. 4, BC: Will AI write scientific papers in the future summary
Day 36: Presentation of cutting-edge work Presentation slides and responses
Nov. 5, 17:00: Learning robot and human collaboration assignment
10 Nov. 8-12 Day 37: Presentation of cutting-edge work Presentation slides and responses
Day 38: Swarm Intelligence
Day 39: AI and the future of work
Day 40: Presentation of cutting-edge work Nov. 12, 17:00: Multi-agent HRC assignment
Wed. Nov. 17, 23:59: Take home final essay
Presentation slides and responses