Transcription of Solving Constraint Satisfaction Problems (CSPs) using Search
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Solving Constraint Satisfaction Problems (CSPs) using Search
Solving Constraint Satisfaction Problems (CSPs) using Search Alan Mackworth UBC CS 322 CSP 2 January 28, 2013 Textbook Lecture Overview Constraint Satisfaction Problems (CSPs): Definition and Recap CSPs: Motivation Solving CSPs - Generate & Test - Graph Search 2 3 Course Overview Environment Problem Type Logic Planning Deterministic Stochastic Constraint Satisfaction Search Arc Consistency Search Search Logics STRIPS Variables + Constraints Variable Elimination bayesian Networks Decision Networks Markov Processes Static Sequential Representation Reasoning Technique Uncertainty Decision Theory Course Module Variable Elimination Value Iteration Planning Now focus on CSPs Standard Search vs. CSP First studied general state space Search in isolation Standard Search problem: Search in a state space State is a black box - any arbitrary data structure that supports three problem-specific routines: goal test: goal(state) finding successor nodes: neighbors(state) if applicable, heuristic evaluation function: h(state) We ll see more specialized versions of Search for various Problems 4 Constraint Satisfaction Problems : State Successor function Goal test Solution Heuristic function Planning : State Successor function Goal test Solution Heuristic function Inference State Successor function Goal test Solution Heuristic function Search in Specific R&R Systems Constraint Satisfact
Bayesian Networks Decision Networks Markov Processes Static Sequential Representation Reasoning Technique Uncertainty Decision Theory Course Module Variable ... • this is now an optimization problem – determine whether some property of the variables holds in all models 17 .
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