Assignments are listed by their due date.
| Week | Dates | Day and Topics | Assignments |
|---|---|---|---|
| 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 |