===== Schedule ======

===== Announcements =====

Links to live MS Teams events:
  * Lectures: [[https://teams.microsoft.com/l/meetup-join/19%3a323d2d59a8f64282b836e440b8cb32d9%40thread.tacv2/1598126257845?context=%7b%22Tid%22%3a%22afb58802-ff7a-4bb1-ab21-367ff2ecfc8b%22%2c%22Oid%22%3a%22bcd6d782-40c2-430e-8091-fd9ebd260de7%22%7d|Tuesdays/Thursdays, 2:00 - 3:15 PM]]
  * Office hours: Apoorv [[https://teams.microsoft.com/l/meetup-join/19%3a323d2d59a8f64282b836e440b8cb32d9%40thread.tacv2/1598300599034?context=%7b%22Tid%22%3a%22afb58802-ff7a-4bb1-ab21-367ff2ecfc8b%22%2c%22Oid%22%3a%22bcd6d782-40c2-430e-8091-fd9ebd260de7%22%7d|Mondays, 2:00 - 4:00 PM]]
  * Office hours: Chaitanya [[https://teams.microsoft.com/l/meetup-join/19%3a323d2d59a8f64282b836e440b8cb32d9%40thread.tacv2/1598301087268?|Fridays, 2:00 - 4:00 PM]]
  * Office hours: Chuck [[https://teams.microsoft.com/l/meetup-join/19%3a323d2d59a8f64282b836e440b8cb32d9%40thread.tacv2/1598288070646?|Wednesdays, 9:00 - 10:00 AM]]
 

Recordings of lecture and office hour videos are available from the Home page of our 
[[https://colostate.instructure.com/courses/109411|Canvas site]].

To use jupyter notebooks on our CS department machines, you must add this line to your .bashrc file:

  export PATH=/usr/local/anaconda/bin:$PATH

This is a tentative schedule of CS440 topics for Fall, 2020.  This will be updated during the summer and as the fall semester continues.


===== August =====

|< 100% 18% 20% 22% 20% 20%  >|
^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
| Week 1:\\  Aug 24 - Aug 28    | What is AI?  Promises and fears.\\ Python review.\\ Problem-Solving Agents.  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/01 Introduction to AI.ipynb|01 Introduction to AI]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/02 Introduction to Python.ipynb|02 Introduction to Python]]   | Chapters 1, 2, 3.1 of Russell and Norvig.\\ Section 1 of [[http://www.scipy-lectures.org|Scipy Lecture Notes]]  \\ [[http://science.sciencemag.org/content/357/6346/7.full|AI, People, and Society]], by Eric Horvitz.\\ [[https://aeon.co/essays/can-we-design-machines-to-make-ethical-decisions|Automated Ethics]], by Tom Chatfield.\\ [[http://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html?_r=0|The Great A.I. Awakening]], by Gideon Lewis-Krause\\ <!-- [[https://www.commondreams.org/news/2017/07/19/fundamental-existential-threat-lawmakers-warned-risks-killer-robots|"Fundamental Existential Threat": Lawmakers Warned of the Risks of Killer Robots]], by Julia Conley\\ -->    |  | 

===== September =====

|< 100% 18% 20% 22% 20% 20%  >|
^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^nderson/cs545/doku.php?id=schedule#september
| Week 2:\\ Aug 31 - Sept 4    | Help with A1.\\ Problem-solving search and how to measure performance.\\ Iterative deepening and other uninformed search methods.   | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/03 Problem-Solving Agents.ipynb|03 Problem-Solving Agents]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/04 Measuring Search Performance.ipynb|04 Measuring Search Performance]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/05 Iterative Deepening and Other Uninformed Search Methods.ipynb|05 Iterative Deepening and Other Uninformed Search Methods]]   | Sections 3.1 - 3.4 of Russell and Norvig  |   | 
| Week 3:\\ Sept 7 - Sept 11  | Informed search. A* search. Python classes, sorting, numpy arrays.  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/06 Python Implementation of Iterative Deepening.ipynb|06 Python Implementation of Iterative Deepening]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/07 Informed Search.ipynb|07 Informed Search]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/08 Python Classes.ipynb|08 Python Classes]]   | Rest of Chapter 3  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A1.1 Uninformed Search.ipynb|A1.1 Uninformed Search]] due Tuesday, Sept. 8, 10:00 PM.  Submit your notebook in Canvas.\\ Here are [[http://www.cs.colostate.edu/~anderson/cs440/notebooks/goodones|good solutions from your classmates]]  |
| Week 4:\\ Sept 14 - Sept 18   | A* optimality, admissible heuristics  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/09 Heuristic Functions.ipynb|09 Heuristic Functions]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/10 Local Search.ipynb|10 Local Search]]   | Chapter 4  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A2.1 Iterative-Deepening Search.ipynb|A2.1 Iterative-Deepening Search]] due Tuesday, Sept. 15, 10:00 PM.\\ Here are [[http://www.cs.colostate.edu/~anderson/cs440/notebooks/goodones|good solutions from your classmates]]  |
| Week 5:\\ Sept 21 - Sept 25   | Effective branching factor.\\ Local search and optimization. Adversarial search. Minimax. Alpha-beta pruning. Stochastic games.  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/11 Adversarial Search.ipynb|11 Adversarial Search]]   | Chapter 5  |
| Week 6:\\ Sept 28 - Oct 2   | Negamax, with pruning. Introduction to Reinforcement Learning.  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/12 Negamax.ipynb|12 Negamax]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/13 Modern Game Playing.ipynb|13 Modern Game Playing]]\\  [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/14 Introduction to Reinforcement Learning.ipynb|14 Introduction to Reinforcement Learning]]      | Chapter 21\\ [[http://incompleteideas.net/book/bookdraft2017nov5.pdf|Reinforcement Learning: An Introduction]]   |   [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A3 A*, IDS, and Effective Branching Factor.ipynb|A3 A*, IDS, and Effective Branching Factor]] due Wednesday, Sept. 30, 10:00 PM.\\ Here are [[http://www.cs.colostate.edu/~anderson/cs440/notebooks/goodones|good solutions from your classmates]]  |

===== October =====

|< 100% 18% 20% 22% 20% 20%  >|
^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
| Week 7:\\ Oct 5 - Oct 9\\ <color red>Oct 8 Lecture will not meet, but recording will be available.</color>  | Reinforcement Learning for Two-Player Games.  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/15 Reinforcement Learning for Two-Player Games.ipynb|15 Reinforcement Learning for Two-Player Games]]   | Chapter 21\\ [[http://incompleteideas.net/book/bookdraft2017nov5.pdf|Reinforcement Learning: An Introduction]]  |  |
| Week 8:\\ Oct 12 - Oct 16  | Constraint satisfaction.\\ Min-conflicts.  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/16 Constraint Satisfaction Problems.ipynb|16 Constraint Satisfaction Problems]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/17 Min-Conflicts.ipynb|17 Min-Conflicts]]  <!-- \\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/25 Min-Conflicts in Python with Examples.ipynb|25 Min-Conflicts in Python with Examples]] -->   | Chapter 6  |
| Week 9:\\ Oct 19 - Oct 23  | Natural language processing.   | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/18 Introduction to Natural Language Processing.ipynb|18 Introduction to Natural Language Processing]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/19 More NLP.ipynb|19 More NLP]] <!-- \\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/27 Word Embeddings.ipynb|27 Word Embeddings]] -->  | [[https://towardsdatascience.com/word-embedding-with-word2vec-and-fasttext-a209c1d3e12c|Word2Vec and FastText Word Embedding with Gensim]]  |  [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A4 Reinforcement Learning Solution To Towers of Hanoi.ipynb|A4 Reinforcement Learning Solution To Towers of Hanoi]] due Tuesday, Oct. 20, 10:00 PM. Here are [[http://www.cs.colostate.edu/~anderson/cs440/notebooks/goodones|good solutions from your classmates]]  |
| Week 10:\\ Oct 26 - Oct 30  | Introduction to Neural Networks  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/20 Introduction to Neural Networks.ipynb|20 Introduction to Neural Networks]]\\  [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/21 Pytorch Neural Networks.ipynb|21 Pytorch Neural Networks]]   <!-- \\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/17 More Introduction to Neural Networks.ipynb|17 More Introduction to Neural Networks]]  -->  | Sections 18.6 and 18.7    | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A5.1 Min-Conflicts.ipynb|A5.1 Min-Conflicts]] due Friday Oct 30, 10:00 PM. Here are [[http://www.cs.colostate.edu/~anderson/cs440/notebooks/goodones|good solutions from your classmates]]   |


===== November =====

|< 100% 18% 20% 22% 20% 20%  >|
^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
| Week 11:\\ Nov 2 - Nov 6  | More Neural Networks  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/22 Classification with Pytorch Neural Networks.ipynb|22 Classification with Pytorch Neural Networks]]  <!-- [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/17 More Introduction to Neural Networks.ipynb|17 More Introduction to Neural Networks]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/22 Autoencoder Neural Networks.ipynb|22 Autoencoder Neural Networks]] -->  |    |     |
| Week 12:\\ Nov 9 - Nov 13  | Interpreting what a neural network has learned.   | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/23 Interpreting What a Neural Network Has Learned.ipynb|23 Interpreting What a Neural Network Has Learned]]   <!-- [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/18 Introduction to Classification.ipynb|18 Introduction to Classification]] -->  |     | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A6 Neural Networks.ipynb|A6 Neural Networks]] due <color red>Sunday Nov 15, 10:00 PM.</color>\\ Here are [[http://www.cs.colostate.edu/~anderson/cs440/notebooks/goodones|good solutions from your classmates]]   |
| Week 13:\\ Nov 16 - Nov 20  | Natural language processing with neural nets.   | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/24 NLP With Transformers.ipynb|24 NLP With Transformers]]  <!-- [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/19 Classification with Linear Logistic Regression.ipynb|19 Classification with Linear Logistic Regression]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/20 Classification with Nonlinear Logistic Regression Using Neural Networks.ipynb|20 Classification with Nonlinear Logistic Regression Using Neural Networks]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/21 Reinforcement Learning with a Neural Network as the Q Function.ipynb|21 Reinforcement Learning with a Neural Network as the Q Function]]  -->  |    |  |
|  Nov 23 - Nov 27  |  Fall Recess!  |

===== December =====

|< 100% 18% 20% 22% 20% 20%  >|
^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
| Week 14:\\ Nov 30 - Dec 4  | Clustering. Word embeddings.\\ Genetic algorithms.  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/25 Clustering of Word Embeddings.ipynb|25 Clustering of Word Embeddings]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/26 Genetic Algorithm Search.ipynb|26 Genetic Algorithm Search]]   |  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A7.1 NLP with Transformers and the T5 Model.ipynb|A7.1 NLP with Transformers and the T5 Model]] due Sunday, Dec 6, 10:00 PM\\ Here are [[http://www.cs.colostate.edu/~anderson/cs440/notebooks/goodones|good solutions from your classmates]]   | 
| Week 15:\\ Dec 7 - Dec 11  | Brain-Computer Interfaces. Pre-training for faster reinforcement learning.   |   |   | 
| Final Exam Week:\\ Dec 14 - Dec 18  | No exam.    |  | | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A8 Report Template.ipynb|A8 Report Template]] due Tuesday, December 15th, 10:00 PM.   |