PPT-Constraint Satisfaction Problems (CSPs)

Introduction and Backtracking Search This lecture topic two lectures Chapter 61 64 except 633 Next lecture topic two lectures Chapter 71 75 Please read lecture topic material before and after each lecture on that topic. Satisfiability. and Constraint Satisfaction Problems. by Carla P. Gomes, Bart Selman, . Nuno. . Crato. and . henry. . Kautz. Presented by . Yunho. Kim. Provable Software Lab, KAIST. Contents. Heavy-Tailed Phenomena in . CSD 15-780: Graduate Artificial Intelligence. Instructors: . Zico. . Kolter. and Zack Rubinstein. TA: Vittorio . Perera. 2. Constraint satisfaction problems. A . constraint satisfaction problem. (CSP): A set of . maximisation. “In today’s tough economic environment it’s more important than ever that CSPs grasp . all. their opportunities to make revenues, and stop leaving money on the table. Paying attention to the bottom line may be essential; but CSPs also urgently need to find ways of maintaining or increasing top line revenues”. . Satisfiability. and Constraint Satisfaction Problems. by Carla P. Gomes, Bart Selman, . Nuno. . Crato. and . henry. . Kautz. Presented by . Yunho. Kim. Provable Software Lab, KAIST. Contents. Heavy-Tailed Phenomena in . Search when states are factored. Until now, we assumed states are black-boxes.. We will now assume that states are made up of “state-variables” and their “values”. Two interesting problem classes. Neil . mcculloch. and Dalia Zileviciute. Energy and economic growth research programme. 3-4 November, Washington . d.c.. The questions and the answers. Is electricity supply a binding constraint to economic growth in developing countries?. Peter J. Stuckey. Overview. Introduction to 433-637. Motivation for constraint programming. Combinatorial optimization . problems . in the real world. Capturing the problem. Introduction to 433-637. Course Website. Problems. (Chapter 6). Two classes of search problems. Assumptions: single agent, deterministic, fully observable, discrete environment. Search for . planning. The path to the goal is the important thing. ). C. onstraint Propagation and Local Search. This lecture topic (two lectures). Chapter 6.1 – 6.4, except 6.3.3. Next lecture topic (two lectures). Chapter 7.1 – 7.5. (Please read lecture topic material before and after each lecture on that topic). Problems. . vs. . . Finite State Problems . Finite . State Problems (FSP). FSP can . be solved by searching in a space of . simple states. . . Finite states are . evaluated by domain-specific heuristics (rules) and tested to see whether they were goal states. . Constraint satisfaction problems (CSPs). Definition:. State. is defined by . variables. . X. i. with . values. from . domain. . D. i. Goal test. . is a set of . constraints. specifying allowable combinations of values for subsets of variables. Dr. Mark H. Mortensen. 66.490.211 and 212. Tues &Thurs 2:00 to 3:15. . 3:30 to 4:45. Manning School of Business. Today. Turn in #4 Dunkin Donuts Case Study. Attendance. Discussion on . SWOT. IIIA-CSIC. Bellaterra, Spain. pedro@iiia.csic.es. 2. Overview. Definitions. Tree. . search. : . backtracking. Arc. . consistency. Hybrids. (. arc. . consistency. + . tree. . search. ): FC, MAC. Neil . mcculloch. and Dalia Zileviciute. Energy and economic growth research programme. 3-4 November, Washington . d.c.. The questions and the answers. Is electricity supply a binding constraint to economic growth in developing countries?.