Instructor: Prof. Steve LaValle, 2107 DCL, lavalle@cs.uiuc.edu

Date  Topics  Materials 
Jan 15  course overview, singlestage decision making, loss, deterministic vs. randomized decisions  Handout: course syllabus 
Jan 17  continuous choice sets, uncertainty, games against nature, observation spaces, Bayes and minimax decision rules  . 
Jan 22  classification, OCR example  . 
Jan 24  parameter estimation, utility theory  . 
Jan 29  criticisms of decision theory, frequentist vs. Bayesian, obtaining priors  . 
Jan 31  multiobjective decision making  . 
Feb 5  multistage decision making, state spaces, additive loss, termination actions  . 
Feb 7  representations (STRIPS, decisiontheoretic, graph), costtocome, costtogo  . 
Feb 12  forward and backwards dynamic programming, relation to Dijkstra  . 
Feb 14  multiplestage games against nature, Markovian models  Handout: Dynamic programming notes: [pdf] [ps] 
Feb 19  feedback strategies, forward projections  . 
Feb 21  dynamic programming  . 
Feb 26  infinite horizon problems  . 
Feb 28  policy iteration, reinforcement learning  Surveys: [Dean] [Kaebling et al.] [Harmon et al.] 
Mar 5  reinforcement learning, imperfect information  . 
Mar 7  observations, information states  . 
Mar 12  MIDTERM EXAM  . 
Mar 26  information space representations  . 
Mar 28  information space representations  . 
Apr 2  examples of informations spaces  . 
Apr 4  Class was cancelled  . 
Apr 9  Solving imperfect state information problems  . 
Apr 11  Twoperson zerosum games  . 
Apr 16  Twoperson zerosum games  . 
Apr 18  Twoperson zerosum games  . 
Apr 23  Nperson nonzerosum games  . 
Apr 25  Nperson nonzerosum games  . 
Apr 30  Perspective  . 
General: