COL333/CSL671 - Artificial Intelligence - Autumn 2015
Tuesday, Thursday, Friday 11-11:50 pm in LH108
(mausam at cse dot iitd dot ac dot in)
Office hours: by appointment, SIT 402
| TAs: (office hours by appointment)
Himanshu Jain (csz138519 at cse.iitd.ac.in)
Yashoteja Prabhu (csz138234 at cse.iitd.ac.in)
Neetu Jindal (neetu at cse.iitd.ac.in)
Ankit Rohilla (mcs142118 at cse.iitd.ac.in)
Harinder Pal (mcs142123 at cse.iitd.ac.in)
Kapil Thakkar (mcs142124 at cse.iitd.ac.in)
Madhur Gupta (cs5110282 at cse.iitd.ac.in)
Mayank Raj (cs5110284 at cse.iitd.ac.in)
Shiva Chandra (cs5110296 at cse.iitd.ac.in)
Karan Goel (ee5110555 at iitd.ac.in)
Shreya Rajpal (me2120800 at iitd.ac.in)
|Start||End||Topics & Lecture Notes||Required Readings||Additional Resources|
|Jul 23||Jul 31||Introduction||AIMA Chapter 1
Beyond Turing Test
Applications of AI
Benefits/Risks of AI
|Aug 4||Aug 7||Uninformed search||AIMA Chapter 3.1-3.4
Intuition of Search Algorithms
Search Algorithms Performance
Uniform Cost Search vs. Djikstra's
|Aug 7||Aug 13||Informed search||AIMA Chapter 3.5-3.7
Depth First Branch and Bound
|Aug 14||Aug 27||Programming Assignment 1||
|Aug 14||Aug 17||Local search||AIMA Chapter 4.1
Stochastic Beam Search
Evolving Monalisa through Genetic Algorithms
Evolving TSP with Genetic Algorithms
Mixability for Genetic Algorithms (pages 66-68)
|Aug 17||Aug 18||Adversarial search||AIMA Chapter 5
How Intelligent is Deep Blue?
Poker is Solved!
|Aug 27||Aug 28||Classical Planning||
AIMA Chapter 10
|Aug 28||Sep 14||Programming Assignment 2|
|Sep 3||Sep 3||Decision Theory||
AIMA Chapter 16.1-16.3, 16.6
|Sep 4||Sep 10||Markov Decision Processes||
AIMA Chapter 17.1-17.3
|Sep 11||Sep 11||Heuristic Search for MDPs||
MDPs Book Chapter 4.1-4.3
|Sep 15||Sep 16||Partially Observable Markov Decision Processes||
AIMA Chapter 17.4
|Sep 16||Sep 29||Programming Assignment 3||
|Sep 17||Sep 29||Reinforcement Learning||
AIMA Chapter 21.1-21.3
||TD Learning for Backgammon
|Oct 1||Oct 6||Bandits and Monte Carlo Tree Search||
Monte Carlo Planning (Sections 3.1-3.3)
AIMA Chapter 21.4
UCT for Go
Monte Carlo Planning
|Oct 4||Oct 28||Programming Assignment 4||
|Oct 13||Oct 16||Logic and Satisfiability||AIMA Chapter 7, 8.1-8.3
|Oct 27||Oct 30||Satisfiability Applications and Phase Transitions||
Advanced SAT Solvers (Section 2.3)
|Oct 28||Nov 12||Programming Assignment 5|
|Oct 29||Oct 29||Intro to Probability||
AIMA Chapter 13
History of Bayes Theorem
|Nov 3||Nov 6||Bayesian Networks Representation||
AIMA Chapter 14.1-14.4
Influence Flow in Bayes Nets
|Nov 6||Nov 10||Bayesian Networks Inference and Learning||
AIMA Chapter 14.5, 20
|Nov 17||Nov 17||Wrap Up|
Stuart Russell & Peter Norvig,
Artificial Intelligence: A Modern Approach,
Prentice-Hall, Third Edition (2009) (required).
Assignments: 50%; Minor (each): 10%; Final: 30%; Class participation, online discussions: extra credit.
There will be five programming assignments due approximately every two weeks.
As adapted from Dan Weld's guidelines.
Collaboration is a very good thing. On the other hand, cheating is considered a very serious offense. Please don't do it! Concern about cheating creates an unpleasant environment for everyone. If you cheat, you get a zero in the assignment, and additionally you risk losing your position as a student in the department and the institute. The department's policy on cheating is to report any cases to the disciplinary committee. What follows afterwards is not fun.
So how do you draw the line between collaboration and cheating? Here's a reasonable set of ground rules. Failure to understand and follow these rules will constitute cheating, and will be dealt with as per institute guidelines.
- The Kyunki Saas Bhi Kabhi Bahu Thi Rule: This rule says that you are free to meet with fellow students(s) and discuss assignments with them. Writing on a board or shared piece of paper is acceptable during the meeting; however, you should not take any written (electronic or otherwise) record away from the meeting. This applies when the assignment is supposed to be an individual effort or whenever two teams discuss common problems they are each encountering (inter-group collaboration). After the meeting, engage in a half hour of mind-numbing activity (like watching an episode of Kyunki Saas Bhi Kabhi Bahu Thi), before starting to work on the assignment. This will assure that you are able to reconstruct what you learned from the meeting, by yourself, using your own brain.
- The Right to Information Rule: To assure that all collaboration is on the level, you must always write the name(s) of your collaborators on your assignment. This also applies when two groups collaborate.