CSCE 420 - Artificial Intelligence

Spring 2022


Professor: Dr. Thomas R. Ioerger
email:ioerger@cs.tamu.edu
office:438 Peterson
office hours:Tues, 1:30-3:00

TA: Jeff Hykin
email address: jeff.hykin@tamu.edu
office hours: Tues, Thurs, 5:15-6:15 (after class)
location: 124 HRBB

Meeting: TR, 3:55-5:10, 124 HRBB

Textbook: Artificial Intelligence: A Modern Approach, 4th US ed. (2020) Stuart Russell and Peter Norvig.

Course Web Page: http://faculty.cs.tamu.edu/ioerger/cs420-spr22/index.html (this page)

Syllabus (contains information about projects, exams, grading policy, etc)

Programming Assignments

The programming assignments will be done (individually) in C++. Students will need to be (and are expected to be) proficient in C++. Programs will have to compile and run on compute.cs.tamu.edu, which is the reference platform. The projects for the course will be submitted via Github.tamu.edu. Students will have to create a (private) repository for this class, and then share that with the instructor and TA by making them collaborators. The date and time students turn in each project will be determined by the timestamp of their commits on their files. It is the student's responsibility to learn how to use Git well enough to commit their code (and reports and other materials required to turn in) and push it to the Github.tamu.edu server. Forgetting or being unable to commit and push their files will not be accepted as an excuse for lateness.

Schedule

topicconceptsreadingassignments
Tues, Jan 18What is AI?perspectives on AI; core concepts Ch. 1; slides
Thurs, Jan 20
Tues Jan 25 Uninformed Search BFS, DFS, iterative deepening Ch. 3; slides
Thur Jan 27complexity analysis, GraphSearch, Uniform Cost
Tues Feb 1 Informed/heuristic Search heuristics, Greedy, A*hand out A1; probs.zip
Thur Feb 3optimality
Tues Feb 8 Iterative Improvement hill-climbing, simulated annealingCh. 4.1; slides
Thur Feb 10genetic algorithms
Tues Feb 15 Game Search minimax, alpha-beta pruningCh. 5; slides
Thur Feb 17board eval functions; Deep Blue
Tues Feb 22 Constraint Satisfactionback-tracking search, CSP heuristics, Ch. 6; slidesA1 due; hand out A2
Thur Feb 24AC-3; min-conflicts
Tues Mar 1Propositional Logic syntax, semantics/models, entailment, ROICh. 7; slides
Thur Mar 3*** exam 1 ***
Tues Mar 8Inference algorithms natural deduction proofs, FC, BC
Thur Mar 10resolution refutation, conversion to CNFA2 due; hand out A3
Tues Mar 15 (Spring Break)
Thur Mar 17 (Spring Break)
Tues Mar 22 Satisfiability DPLL; hard problems; WalkSAT
Thur Mar 24 FOL syntax, semantics (models), ontologiesCh. 8; slides
Tues Mar 29 Inference in FOL Rules of Inference, unification, Natural Deduction proofsCh. 9A3 due; hand out A4
Thur Mar 31 Resolution in FOL, conversion to CNF, Herbrand's Theorem
Tues Apr 5 Forward-chaining; Backward-chaining
Thur Apr 7 PROLOGProlog slides, Prolog mini-tutorial
Tues Apr 12 Uncertainty default reasoning, nonmonotonic logics, negation in PrologCh. 10.6 slides
Thur Apr 14Probabilistic Knowledge Representation, Bayes' RuleCh. 12 (skip 12.6-7) hand out A5
Tues Apr 19Planning Sit Calc, Frame Prob, PDDL, Forward SSSCh. 11 (skip 11.3-11.5); slidesA4 due
Thur Apr 21goal regression; other types of planners
Tues Apr 26 Intelligent AgentsCh. 2; slidesA5 due (3:55pm) solutions HARD DEADLINE, NO LATE HOMEWORKS ACCEPTED
hand out A6
Thur Apr 28: ***exam 2***
Mon, May 9, 3:00pm(finals week)Assignment A6 due at 3:00pm