CS440: Introduction to Artificial Intelligence

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start [2017/08/23 08:53]
anderson [October] 		start [2020/12/08 14:01]
anderson [December]
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-====== Schedule ======+===== Schedule ======
  
 ===== Announcements ===== ===== 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]]
 + 
  
-Lecture videos are available from the Canvas site (in the menu on the left) by selecting [[https://colostate.instructure.com/courses/55296/external_tools/2755|Echo 360]].+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: 
-are available at this [[https://echo.colostate.edu/ess/portal/section/a5759ae3-82dc-43df-b515-dd944a6c4976|CS480 video recordings site]]. + 
-*/+  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 ===== ===== August =====
  
-|< 100% 10% 20% 30% 20% 20%  >|+|< 100% 18% 20% 22% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^ ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 1:\\  Aug 21 - Aug 25    | What is AI?  Promises and fears.\\ Python review.\\ Problem-Solving Agents.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/01 Introduction to AI.ipynb|01 Introduction to AI]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/02 Introduction to Python.ipynb|02 Introduction to Python]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/03 Problem-Solving Agents.ipynb|03 Problem-Solving Agents]]   | Chapters 1, 2, 3.1.\\ [[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, NYT, Dec 14, 2016.\\ [[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\\ Section 1 of [[http://www.scipy-lectures.org|Scipy Lecture Notes]]   |  |  +| Week 1:\\  Aug 24 - Aug 28    | What is AI?  Promises and fears.\\ Python review.\\ Problem-Solving Agents.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/01 Introduction to AI.ipynb|01 Introduction to AI]]\\ [[http://nbviewer.ipython.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\\ -->    |  | 
-| Week 2:\\ Aug 28 - Sept 1    |  Problem-solving search and how to measure performance.\\ Iterative deepening and other uninformed search methods.   |     | Sections 3.1 - 3.4  |    +
  
 ===== September ===== ===== September =====
  
-|< 100% 10% 20% 30% 20% 20%  >| +|< 100% 18% 20% 22% 20% 20%  >| 
-^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^ +^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^nderson/cs545/doku.php?id=schedule#september 
-| Week 3:\\ Sept 4 - Sept 8  | Informed search. A* search. Python classes, sorting, numpy arrays.  |  | Rest of Chapter 3  | +| Week 2:\\ Aug 31 - Sept 4    | Help with A1.\\ Problem-solving search and how to measure performance.\\ Iterative deepening and other uninformed search methods.   | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/03 Problem-Solving Agents.ipynb|03 Problem-Solving Agents]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/04 Measuring Search Performance.ipynb|04 Measuring Search Performance]]\\ [[http://nbviewer.ipython.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 4:\\ Sept 11 - Sept 15   |  A* optimality, admissible heuristics, effective branching factor.\\ Local search and optimization.  |  | Chapter 4  | +| Week 3:\\ Sept 7 - Sept 11  | Informed search. A* search. Python classes, sorting, numpy arrays.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/06 Python Implementation of Iterative Deepening.ipynb|06 Python Implementation of Iterative Deepening]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/07 Informed Search.ipynb|07 Informed Search]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/08 Python Classes.ipynb|08 Python Classes]]   | Rest of Chapter 3  | [[http://nbviewer.ipython.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 5:\\ Sept 18 - Sept 22   | Adversarial search. Minimax. Alpha-beta pruning. Negamax, with pruning.  |  | Chapter 5  | +| Week 4:\\ Sept 14 - Sept 18   | A* optimality, admissible heuristics  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/09 Heuristic Functions.ipynb|09 Heuristic Functions]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/10 Local Search.ipynb|10 Local Search]]   | Chapter 4  | [[http://nbviewer.ipython.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 6:\\ Sept 25 - Sept 29   | Stochastic games. Expectimax. |  | Sections 5.5 - 5.6 |+| Week 5:\\ Sept 21 - Sept 25   | Effective branching factor.\\ Local search and optimization. Adversarial search. Minimax. Alpha-beta pruning. Stochastic games.  | [[http://nbviewer.ipython.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.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/12 Negamax.ipynb|12 Negamax]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/13 Modern Game Playing.ipynb|13 Modern Game Playing]]\\  [[http://nbviewer.ipython.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]]   |   [[http://nbviewer.ipython.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 ===== ===== October =====
  
-|< 100% 10% 20% 30% 20% 20%  >|+|< 100% 18% 20% 22% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^ ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 7:\\ Oct 2 - Oct 6  | Introduction to Reinforcement Learning.  |  | Chapter 21\\ [[http://incompleteideas.net/sutton/book/the-book-2nd.html|Reinforcement Learning: An Introduction]]\\ [[http://www.springerlink.com/content/q04392v367885456/|Reinforcement Learning in Games]]  | +| 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.  | [[http://nbviewer.ipython.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 9 - Oct 13  | Constraint satisfaction. Min-conflicts  |  | Chapter 6.\\ [[http://dl.acm.org/citation.cfm?id=1928809|A new iterated local search algorithm for solving broadcast scheduling problems in packet radio networks]]  | +| Week 8:\\ Oct 12 - Oct 16  | Constraint satisfaction.\\ Min-conflicts.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/16 Constraint Satisfaction Problems.ipynb|16 Constraint Satisfaction Problems]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/17 Min-Conflicts.ipynb|17 Min-Conflicts]]  <!-- \\ [[http://nbviewer.ipython.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 16 - Oct 20  | Propositional and First-Order Logic. Introduction to Prolog.  |  | Chapters 7, 8, 9  | +| Week 9:\\ Oct 19 - Oct 23  | Natural language processing.   | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/18 Introduction to Natural Language Processing.ipynb|18 Introduction to Natural Language Processing]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/19 More NLP.ipynb|19 More NLP]] <!-- \\ [[http://nbviewer.ipython.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]]  |  [[http://nbviewer.ipython.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 23 - Oct 27  |  |  |  |+| Week 10:\\ Oct 26 - Oct 30  | Introduction to Neural Networks  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/20 Introduction to Neural Networks.ipynb|20 Introduction to Neural Networks]]\\  [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/21 Pytorch Neural Networks.ipynb|21 Pytorch Neural Networks]]   <!-- \\ [[http://nbviewer.ipython.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    | [[http://nbviewer.ipython.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 ===== ===== November =====
  
-|< 100% 10% 20% 30% 20% 20%  >|+|< 100% 18% 20% 22% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^ ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 11:\\ Oct 30 - Nov 3  |   |  |  | +| Week 11:\\ Nov 2 - Nov 6  | More Neural Networks  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/22 Classification with Pytorch Neural Networks.ipynb|22 Classification with Pytorch Neural Networks]]  <!-- [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/17 More Introduction to Neural Networks.ipynb|17 More Introduction to Neural Networks]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/22 Autoencoder Neural Networks.ipynb|22 Autoencoder Neural Networks]] -->  |    |     | 
-| Week 12:\\ Nov 6 - Nov 10  |  |  |  | +| Week 12:\\ Nov 9 - Nov 13  | Interpreting what a neural network has learned.   | [[http://nbviewer.ipython.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]]   <!-- [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/18 Introduction to Classification.ipynb|18 Introduction to Classification]] -->  |     | [[http://nbviewer.ipython.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 13 - Nov 17  |  |  |  | +| Week 13:\\ Nov 16 - Nov 20  | Natural language processing with neural nets.   | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/24 NLP With Transformers.ipynb|24 NLP With Transformers]]  <!-- [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/19 Classification with Linear Logistic Regression.ipynb|19 Classification with Linear Logistic Regression]]\\ [[http://nbviewer.ipython.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]]\\ [[http://nbviewer.ipython.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 20 - Nov 24  |  Fall Break  | +|  Nov 23 - Nov 27  |  Fall Recess!  |
-| Week 14:\\ Nov 27 - Dec 1  |  |  |  |+
  
 ===== December ===== ===== December =====
  
-|< 100% 10% 20% 30% 20% 20%  >|+|< 100% 18% 20% 22% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^ ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 15:\\ Dec 4 - Dec 8  |  |  |  | +| Week 14:\\ Nov 30 - Dec 4  | Clustering. Word embeddings.\\ Genetic algorithms.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/25 Clustering of Word Embeddings.ipynb|25 Clustering of Word Embeddings]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/26 Genetic Algorithm Search.ipynb|26 Genetic Algorithm Search]]   |  | [[http://nbviewer.ipython.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   |  
-| Finals Week:\\ Dec 11 - Dec 15  |   |  |  |+| Week 15:\\ Dec 7 - Dec 11  | Brain-Computer Interfaces  |   |   |  
 +| Final Exam Week:\\ Dec 14 - Dec 18  | No exam.    |  | | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A8 Report Template.ipynb|A8 Report Template]] due Tuesday, December 15th, 10:00 PM.   | 
 + 
  
  
  
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