PPT-Min-Conflicts Heuristic for Solving Constraint Satisfaction Problems

Rhea McCaslin The GDS Network Guarded Discrete Stochastic neural network developed by Johnston and Adorf 2 Hubble Space Telescope Scheduling Problem PROBLEM Between 10000 30000 astronomical observations per year . Heuristic - a “rule of thumb” used to help guide search. often, something learned experientially and recalled when needed. Heuristic Function - function applied to a state in a search space to indicate a likelihood of success if that state is selected. Introduction and Backtracking Search. This lecture:. CSP Introduction and Backtracking Search. Chapter 6.1 – 6.4, except 6.3.3. Next lecture:. CSP Constraint Propagation & Local Search. Chapter 6.1 – 6.4, except 6.3.3. 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 . Bmin/A min *maj Bmin/A min *maj n7* Bmin/A min n7* Bmin/A min *maj n7F *maj *maj *maj n7Bm Bmin/A min *maj n7* Bmin/A min *maj n7F *maj n7Bm *maj n7Bm *maj n7Bm */A A/* n11Bmin *maj AWA add9 Ain't No 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. Heuristic - a “rule of thumb” used to help guide search. often, something learned experientially and recalled when needed. Heuristic Function - function applied to a state in a search space to indicate a likelihood of success if that state is selected. Oliver Lum, . Xingyin. Wang, Ping Chen, Bruce Golden, Edward . Wasil. 1. Swap-Body VRP. Q = swap-body . capacity. Truck. Train. Models scenario in which the vehicles have detachable components, and certain customers may be visited by only the smallest vehicle possible (due to space constraints). Introduction and Backtracking 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. . NPT Test Gauges TOO SIMILIAR to Riser Margin For Crew To Ignore. Pressure of Reservoir Pushing “UP” is . ~1,400 psi. Pressure of Riser Mud Pushing “DOWN” is . ~1,400 psi. Water Depth. 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. . Continued. Before we continue. Breadth-First. Depth-First. Uniform Cost. Iterative-Deepening. Before we continue. Breadth-First. S,A,B,D,C,G. Depth-First. S,A,C,D,B,G. Uniform Cost. S,A,B,D,C,G. Iterative-Deepening. is collaborating with JSTOR to digitize preserve and extend access to7KH3KLHOWDDSSDQhttp//wwwjstororgKDWV3UREOHP6ROYLQJXWKRUVf0LFKDHO0DUWLQH6RXUFH7KH3KLHOWDDSSDQ9RO1RSUfSS3XEOLVKHGE3KLHOWDDSSDQWHUQDWL often, something learned experientially and recalled when needed. Heuristic Function - function applied to a state in a search space to indicate a likelihood of success if that state is selected. heuristic search methods are known as “weak methods” because of their generality and because they do not apply a great deal of knowledge .