*Constraint satisfaction Wikipedia Problem Solving in Artificial Intelligence 4810-1208 Philippe Codognet. SHORT INTRODUCTION TO THE COURSE TOPICS. вЂ“ In computer science and in the part of artificial intelligence that deals with algorithms, problem solving encompasses a Constraint Satisfaction Problems (CSP) 7. Combinatorial Optimization Problems 8. Local Search techniques*

The complexity of constraint satisfaction revisited. Problem Solving in Artificial Intelligence 4810-1208 Philippe Codognet. SHORT INTRODUCTION TO THE COURSE TOPICS. вЂ“ In computer science and in the part of artificial intelligence that deals with algorithms, problem solving encompasses a Constraint Satisfaction Problems (CSP) 7. Combinatorial Optimization Problems 8. Local Search techniques, tion problem. The next section presents some extensions of the constraint satisfaction problem that allow to п¬Ѓnd an optimal solution. Finally, a constraint logic programming paradigm is introduced as one of the most common environments for solving constraint satisfaction problems. 2.1 Constraint Satisfaction Problem.

Artificial Intelligence: Constraint satisfaction problems 5 Constraint satisfaction problem Search in games Chess and cognition The mГ©nage problem the number of different ways in which it is possible to seat a set of male-female couples at a dining inputs: csp, a constraint satisfaction problem max_steps, the number of steps allowed Constraint Satisfaction Problems (CSPs) 5 Previously: generic search вЂ“ state is a вЂњblack boxвЂќ вЂ“ state must support goal test, eval, successor CSP вЂ“ stateis deп¬Ѓned byvariables X i withvaluesfromdomain D i вЂ“ goal testis a set ofconstraintsspecifying allowable combinations of values for subsets of variables

Artiп¬Ѓcial Intelligence Constraint Satisfaction Problems Marc Toussaint University of Stuttgart design approximate constraint propagation for speciп¬Ѓc problem E.g.: Sudoku: If X i is assigned, Artificial Intelligence Constraint Satisfaction Problems CSC384: Intro to Artificial Intelligence Backtracking Search I Announcements Hojjat Ghaderi [Courtesy of Fahiem Bacchus], University of Toronto, Fall 2006 2 Constraint Satisfaction Problems Many problems can be represented as a search for a vector of feature values. k-features: variables. Each feature has a value. Domain of values for the

Constraint Propagation in line labelling One of the most elegant AI applications of constraint satisfaction is junction and line labelling in computer vision, an example of symbolic, rather than numeric, constraint propagation. [] Constraint solving is one of the biggest success stories in Artificial Intelligence. [] The complexity of constraint satisfaction revisited 59 One of the key insights of arc consistency for FCSPs can be found in Fikes' paper in the very first issue of Artificial Intelligence [6]; in particular, if a value, c, for one problem variable is inconsistent with all values for

Problem Solving in Artificial Intelligence 4810-1208 Philippe Codognet. SHORT INTRODUCTION TO THE COURSE TOPICS. вЂ“ In computer science and in the part of artificial intelligence that deals with algorithms, problem solving encompasses a Constraint Satisfaction Problems (CSP) 7. Combinatorial Optimization Problems 8. Local Search techniques 5 CONSTRAINT SATISFACTION PROBLEMS In which we see how treating states as more than just little black boxes leads to the invention of a range of powerful new search methods and a deeper understanding of problem structure and complexity.

Full text of the second edition of Artificial Intelligence: foundations of computational agents, Cambridge University Press, 2017 is now available. 4.2.2 Constraint Satisfaction Problems. A constraint satisfaction problem (CSP) consists of a set of variables, вЂў Example of a Constraint Satisfaction Problem (CSP) вЂў Representing a CSP вЂў Solving a CSP вЂ“ Backtracking searchBacktracking search Constraint Loggg gic Programming вЂў A constraint logic program is a logic program that contains constraints in the body of clauses A(X,Y) :-X+Y>0, B(X), C(Y) Constraints are stored in a constraint store

вЂў Example of a Constraint Satisfaction Problem (CSP) вЂў Representing a CSP вЂў Solving a CSP вЂ“ Backtracking searchBacktracking search Constraint Loggg gic Programming вЂў A constraint logic program is a logic program that contains constraints in the body of clauses A(X,Y) :-X+Y>0, B(X), C(Y) Constraints are stored in a constraint store Artiп¬Ѓcial Intelligence Constraint Satisfaction Problems Marc Toussaint University of Stuttgart Winter 2018/19 (slides based on Stuart RussellвЂ™s AI course) Motivation: Constraint Satisfaction Problems { Problem Formulation & Examples { 3/29. Constraint satisfaction problems (CSPs) In previous lectures we considered sequential decision

Constraint Propagation in line labelling One of the most elegant AI applications of constraint satisfaction is junction and line labelling in computer vision, an example of symbolic, rather than numeric, constraint propagation. [] Constraint solving is one of the biggest success stories in Artificial Intelligence. [] thekhushishah / Artificial-Intelligence. Watch 0 Star 1 Fork 3 Code. Issues 0. Pull requests 0. Actions Projects 0. Security Insights Code. Issues 0. Pull requests 0. Projects 0. Artificial-Intelligence / constraint_satisfaction_problem.pdf. Find file Copy path Fetching contributorsвЂ¦ Cannot retrieve contributors at this time. 462 KB

Artificial Intelligence Methods вЂ“ WS 2005/2006 вЂ“ Marc Erich Latoschik Outline вЂў Constraint Satisfaction Problems (CSP) вЂў Backtracking search for CSPs вЂў Local search for CSPs Artificial Intelligence Methods вЂ“ WS 2005/2006 вЂ“ Marc Erich Latoschik Constraint satisfaction problems (CSPs) вЂў вЂ¦ Constraint propagation (e.g., arc consistency) does additional work to constrain values and detect inconsistencies The CSP representation allows analysis of problem structure Tree-structured CSPs can be solved in linear time Iterative min-con icts is usually e ective in practice Chapter 5 40

* Constraint (Artificial Intelligence) Definition. Characteristics of Artificial Intelligence: Artificial Intelligence (AI) is a branch of Science which deals with helping machines find solutions to complex problems in a more human-like fashion. This generally involves borrowing characteristics from human intelligence and applying them as algorithms in a computer-friendly way., A large number of problems in AI and other areas of computer science can be viewed as special cases of the constraint-satisfaction problem. Some examples are machine vision, belief maintenance, scheduling, temporal reasoning, graph problems, floor plan design, the planning of genetic experiments, and the satisfiability problem..

Constraint Satisfaction Problems Wiley Online Books. Artificial Intelligence: Constraint satisfaction problems 5 Constraint satisfaction problem Search in games Chess and cognition The mГ©nage problem the number of different ways in which it is possible to seat a set of male-female couples at a dining inputs: csp, a constraint satisfaction problem max_steps, the number of steps allowed, Sep 05, 2016В В· Constraint satisfaction problems are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations. CSPs represent the entities in a problem as.

Constraint Satisfaction Problem Intellipaat Community. thekhushishah / Artificial-Intelligence. Watch 0 Star 1 Fork 3 Code. Issues 0. Pull requests 0. Actions Projects 0. Security Insights Code. Issues 0. Pull requests 0. Projects 0. Artificial-Intelligence / constraint_satisfaction_problem.pdf. Find file Copy path Fetching contributorsвЂ¦ Cannot retrieve contributors at this time. 462 KB CSC384: Intro to Artificial Intelligence Backtracking Search I Announcements Hojjat Ghaderi [Courtesy of Fahiem Bacchus], University of Toronto, Fall 2006 2 Constraint Satisfaction Problems Many problems can be represented as a search for a vector of feature values. k-features: variables. Each feature has a value. Domain of values for the.

CSC384: Intro to Artificial Intelligence Backtracking Search I Announcements Hojjat Ghaderi [Courtesy of Fahiem Bacchus], University of Toronto, Fall 2006 2 Constraint Satisfaction Problems Many problems can be represented as a search for a vector of feature values. k-features: variables. Each feature has a value. Domain of values for the 5 CONSTRAINT SATISFACTION PROBLEMS In which we see how treating states as more than just little black boxes leads to the invention of a range of powerful new search methods and a deeper understanding of problem structure and complexity. Chapters 3 and 4 explored the idea that problems can be solved by searching in a space of states.

tion problem. The next section presents some extensions of the constraint satisfaction problem that allow to п¬Ѓnd an optimal solution. Finally, a constraint logic programming paradigm is introduced as one of the most common environments for solving constraint satisfaction problems. 2.1 Constraint Satisfaction Problem Algorithms for Constraint Satisfaction Problems: A Survey problems in Artificial Intelligence and other areas of computer science can be viewed as a special case of the constraint satisfaction

Constraint-based problems are hard combinatorial problems and are usually solved by heuristic search methods. In this paper, we consider applying a machine learning approach to improve the performance of these search-based solvers. We apply reinforcement learning in the context of Constraint Satisfaction Problems (CSP) to learn a value function, which results in a novel solving вЂ¦ Constraint Satisfaction in Artificial Intelligence - Chapter Summary. This handy chapter on constraint satisfaction in artificial intelligence was created by professional instructors to make these

A large number of problems in AI and other areas of computer science can be viewed as special cases of the constraint-satisfaction problem. Some examples are machine vision, belief maintenance, scheduling, temporal reasoning, graph problems, floor plan design, the planning of genetic experiments, and the satisfiability problem. A large number of problems in AI and other areas of computer science can be viewed as special cases of the constraint-satisfaction problem. Some examples are machine vision, belief maintenance, scheduling, temporal reasoning, graph problems, floor plan design, the planning of genetic experiments, and the satisfiability problem.

Artiп¬Ѓcial Intelligence Constraint Satisfaction Problems Marc Toussaint University of Stuttgart design approximate constraint propagation for speciп¬Ѓc problem E.g.: Sudoku: If X i is assigned, Artificial Intelligence Constraint Satisfaction Problems Artificial Intelligence: Constraint satisfaction problems 5 Constraint satisfaction problem Search in games Chess and cognition The mГ©nage problem the number of different ways in which it is possible to seat a set of male-female couples at a dining inputs: csp, a constraint satisfaction problem max_steps, the number of steps allowed

Constraint Satisfaction Problems This problem: A binary CSP: вЂў each constraint relates two variables. CIS 391 - Intro to AI 9 Varieties of CSPs Intro to Artificial Intelligence) A1 A3 A2 The image of the same vertex from a different point of view gives a different junction type. Constraint satisfaction is the group of problems in which finding the solution involves discovering a suitable group of parameters such that the that result falls with some pre-defined boundaries. Many real-world problems can be described as constraint satisfaction problems (CSPs).

Algorithms for Constraint Satisfaction Problems: A Survey problems in Artificial Intelligence and other areas of computer science can be viewed as a special case of the constraint satisfaction Characteristics of Artificial Intelligence: Artificial Intelligence (AI) is a branch of Science which deals with helping machines find solutions to complex problems in a more human-like fashion. This generally involves borrowing characteristics from human intelligence and applying them as algorithms in a computer-friendly way.

Constraint Satisfaction in Artificial Intelligence - Chapter Summary. This handy chapter on constraint satisfaction in artificial intelligence was created by professional instructors to make these Artificial Intelligence: Constraint satisfaction problems 5 Constraint satisfaction problem Search in games Chess and cognition The mГ©nage problem the number of different ways in which it is possible to seat a set of male-female couples at a dining inputs: csp, a constraint satisfaction problem max_steps, the number of steps allowed

Constraint Satisfaction Problems This problem: A binary CSP: вЂў each constraint relates two variables. CIS 391 - Intro to AI 9 Varieties of CSPs Intro to Artificial Intelligence) A1 A3 A2 The image of the same vertex from a different point of view gives a different junction type. Constraint propagation (e.g., arc consistency) does additional work to constrain values and detect inconsistencies The CSP representation allows analysis of problem structure Tree-structured CSPs can be solved in linear time Iterative min-con icts is usually e ective in practice Chapter 5 40

Constraint satisfaction is the group of problems in which finding the solution involves discovering a suitable group of parameters such that the that result falls with some pre-defined boundaries. Many real-world problems can be described as constraint satisfaction problems (CSPs). Mar 13, 2018В В· в† constraint satisfaction is problem solving technique. It is a finite choices decision problem. Where one is given a fixed set of decisions to make . Each decision involves choosing among a

(PDF) Learning While Searching in Constraint-Satisfaction. 5 CONSTRAINT SATISFACTION PROBLEMS In which we see how treating states as more than just little black boxes leads to the invention of a range of powerful new search methods and a deeper understanding of problem structure and complexity., Researchers in artificial intelligence (AI) usually adopt a constraint satisfaction approach as their preferred method when tackling such problems. However, constraint satisfaction approaches are not widely known amongst operational researchers. The aim of this paper is to introduce constraint satisfaction to the operational researcher..

Constraint satisfaction problems Algorithms and. Jan 31, 2020В В· It may be nice to have series of short videos on how to install and/or how to use with a few small examples. One can create these videos using screen recording utilities (such as вЂ¦, To work on this problem set, you will need to get the code: Constraint Satisfaction Problems . In this portion of Lab 4, you are to complete the implementation of a general constraint satisfaction problem solver. You'll test it on problems we've worked out by hand in class. 6.034 Artificial Intelligence.

The complexity of constraint satisfaction revisited 59 One of the key insights of arc consistency for FCSPs can be found in Fikes' paper in the very first issue of Artificial Intelligence [6]; in particular, if a value, c, for one problem variable is inconsistent with all values for Algorithms for Constraint Satisfaction Problems: A Survey problems in Artificial Intelligence and other areas of computer science can be viewed as a special case of the constraint satisfaction

The complexity of constraint satisfaction revisited 59 One of the key insights of arc consistency for FCSPs can be found in Fikes' paper in the very first issue of Artificial Intelligence [6]; in particular, if a value, c, for one problem variable is inconsistent with all values for Characteristics of Artificial Intelligence: Artificial Intelligence (AI) is a branch of Science which deals with helping machines find solutions to complex problems in a more human-like fashion. This generally involves borrowing characteristics from human intelligence and applying them as algorithms in a computer-friendly way.

Constraint Satisfaction Problems This problem: A binary CSP: вЂў each constraint relates two variables. CIS 391 - Intro to AI 9 Varieties of CSPs Intro to Artificial Intelligence) A1 A3 A2 The image of the same vertex from a different point of view gives a different junction type. I'm struggling my way through Artificial Intelligence: A Modern Approach in order to alleviate my natural stupidity. In trying to solve some of the exercises, I've come up against the "Who Owns the Zebra" problem, Exercise 5.13 in Chapter 5.This has been a topic here on SO but the responses mostly addressed the question "how would you solve this if you had a free choice of problem solving

Algorithms and Ordering Heuristics for Distributed Constraint Satisfaction Problems. A wide variety of problems in artificial intelligence are solved using the constraint satisfaction problem paradigm. However, there are several applications in multi-agent coordination that are of a distributed nature. tion problem. The next section presents some extensions of the constraint satisfaction problem that allow to п¬Ѓnd an optimal solution. Finally, a constraint logic programming paradigm is introduced as one of the most common environments for solving constraint satisfaction problems. 2.1 Constraint Satisfaction Problem

Course on Articial Intelligence, summer term 2007 11/ 31 Articial Intelligence 1. Constraint Satisfaction Problems 2. Backtracking Search 3. Local Search 4. The Structure of Problems Lars Schmidt-Thieme, Information Systems and Machine Learning Lab (ISMLL), University of Hildesheim, Germany, Course on Articial Intelligence, summer term 2007 12/ 31 Learning While Searching in Constraint-Satisfaction-Problems. Proceedings of the 5th National Conference on Artificial Intelligence. LEARNING WHILE SEARCHING IN CONSTRAINT-SATISFACTION

tion problem. The next section presents some extensions of the constraint satisfaction problem that allow to п¬Ѓnd an optimal solution. Finally, a constraint logic programming paradigm is introduced as one of the most common environments for solving constraint satisfaction problems. 2.1 Constraint Satisfaction Problem I'm struggling my way through Artificial Intelligence: A Modern Approach in order to alleviate my natural stupidity. In trying to solve some of the exercises, I've come up against the "Who Owns the Zebra" problem, Exercise 5.13 in Chapter 5.This has been a topic here on SO but the responses mostly addressed the question "how would you solve this if you had a free choice of problem solving

E&CE 457 Applied Artificial Intelligence Page 2 Constraint Satisfaction Problems (CSP) An ASSIGNMENT of values to ALL variables that does NOT violate any constraints is said to be CONSISTENT. GOAL is to find a CONSISTENT ASSIGNMENT (if one exists). If a GOAL does not exist, perhaps we can say why (i.e., proof of INCONSISTENCY). Constraint satisfaction is the group of problems in which finding the solution involves discovering a suitable group of parameters such that the that result falls with some pre-defined boundaries. Many real-world problems can be described as constraint satisfaction problems (CSPs).

Constraint-based problems are hard combinatorial problems and are usually solved by heuristic search methods. In this paper, we consider applying a machine learning approach to improve the performance of these search-based solvers. We apply reinforcement learning in the context of Constraint Satisfaction Problems (CSP) to learn a value function, which results in a novel solving вЂ¦ thekhushishah / Artificial-Intelligence. Watch 0 Star 1 Fork 3 Code. Issues 0. Pull requests 0. Actions Projects 0. Security Insights Code. Issues 0. Pull requests 0. Projects 0. Artificial-Intelligence / constraint_satisfaction_problem.pdf. Find file Copy path Fetching contributorsвЂ¦ Cannot retrieve contributors at this time. 462 KB

Constraint propagation (e.g., arc consistency) does additional work to constrain values and detect inconsistencies The CSP representation allows analysis of problem structure Tree-structured CSPs can be solved in linear time Iterative min-con icts is usually e ective in practice Chapter 5 40 The complexity of constraint satisfaction revisited 59 One of the key insights of arc consistency for FCSPs can be found in Fikes' paper in the very first issue of Artificial Intelligence [6]; in particular, if a value, c, for one problem variable is inconsistent with all values for

constraint satisfaction problem. вЂў A Constraint Satisfaction Problem consists of 3 components 1. A set of variables. 2. A set of values for each of the variables. 3. A set of constraints between various collections of variables. We must find a value for each of the variables that satisfies all of the constraints. Jan 31, 2020В В· It may be nice to have series of short videos on how to install and/or how to use with a few small examples. One can create these videos using screen recording utilities (such as вЂ¦

Constraint Satisfaction Problems (CSP). Artificial Intelligence Methods вЂ“ WS 2005/2006 вЂ“ Marc Erich Latoschik Outline вЂў Constraint Satisfaction Problems (CSP) вЂў Backtracking search for CSPs вЂў Local search for CSPs Artificial Intelligence Methods вЂ“ WS 2005/2006 вЂ“ Marc Erich Latoschik Constraint satisfaction problems (CSPs) вЂў вЂ¦, Foundations of Artificial Intelligence Bart Selman selman@cs.cornell.edu Module: Constraint Satisfaction Chapter 6, R&N (Completes part II вЂ“ Problem Solving) Bart Selman CS4700 2 Outline Constraint Satisfaction Problems (CSP) Backtracking search for CSPs ..

Constraint Satisfaction Problems (CSP). Problem Solving in Artificial Intelligence 4810-1208 Philippe Codognet. SHORT INTRODUCTION TO THE COURSE TOPICS. вЂ“ In computer science and in the part of artificial intelligence that deals with algorithms, problem solving encompasses a Constraint Satisfaction Problems (CSP) 7. Combinatorial Optimization Problems 8. Local Search techniques The complexity of constraint satisfaction revisited 59 One of the key insights of arc consistency for FCSPs can be found in Fikes' paper in the very first issue of Artificial Intelligence [6]; in particular, if a value, c, for one problem variable is inconsistent with all values for.

Constraint satisfaction problems are characterized by definition and example. The essential algorithm and underlying mathematics for implementing constraint satisfaction in artificial neural networks are described, along with notable variations. Work on symbolic constraint satisfaction in Artificial Intelligence is discussed briefly. Full text of the second edition of Artificial Intelligence: foundations of computational agents, Cambridge University Press, 2017 is now available. 4.2.2 Constraint Satisfaction Problems. A constraint satisfaction problem (CSP) consists of a set of variables,

Oct 13, 2015В В· TLo (IRIDIA) 50October 13, 2015 Local search for CSP function MIN-CONFLICTS(csp, max_steps) return solution or failure inputs: csp, a constraint satisfaction problem max_steps, the number of steps allowed before giving up current в†ђ an initial complete assignment for csp for i = 1 to max_steps do if current is a solution for csp then return Jul 04, 2019В В· I'm struggling my way through Artificial Intelligence: A Modern Approach in order to alleviate my natural stupidity. In trying to solve some of the exercises, I've come up against the "Who Owns the Zebra" problem, Exercise 5.13 in Chapter 5.. I accept that Prolog is a very appropriate programming language for this kind of problem, and there are some fine packages available, e.g. in вЂ¦

5 CONSTRAINT SATISFACTION PROBLEMS In which we see how treating states as more than just little black boxes leads to the invention of a range of powerful new search methods and a deeper understanding of problem structure and complexity. Chapters 3 and 4 explored the idea that problems can be solved by searching in a space of states. вЂњConstraint Satisfaction Problems,вЂќ Artificial Intelligence, Spring, 2010 Constraint Satisfaction Problems CSP is defined by a set of variables X1, X2, вЂ¦, Xn, each has a nonempty domain Di of possible values ; a set of constraints , C1, C2, вЂ¦, Cm, each involves some subset of the variables and the allowable combinations of values for

Problem Solving in Artificial Intelligence 4810-1208 Philippe Codognet. SHORT INTRODUCTION TO THE COURSE TOPICS. вЂ“ In computer science and in the part of artificial intelligence that deals with algorithms, problem solving encompasses a Constraint Satisfaction Problems (CSP) 7. Combinatorial Optimization Problems 8. Local Search techniques tion problem. The next section presents some extensions of the constraint satisfaction problem that allow to п¬Ѓnd an optimal solution. Finally, a constraint logic programming paradigm is introduced as one of the most common environments for solving constraint satisfaction problems. 2.1 Constraint Satisfaction Problem

5 CONSTRAINT SATISFACTION PROBLEMS In which we see how treating states as more than just little black boxes leads to the invention of a range of powerful new search methods and a deeper understanding of problem structure and complexity. Chapters 3 and 4 explored the idea that problems can be solved by searching in a space of states. Constraint Propagation in line labelling One of the most elegant AI applications of constraint satisfaction is junction and line labelling in computer vision, an example of symbolic, rather than numeric, constraint propagation. [] Constraint solving is one of the biggest success stories in Artificial Intelligence. []

вЂў Example of a Constraint Satisfaction Problem (CSP) вЂў Representing a CSP вЂў Solving a CSP вЂ“ Backtracking searchBacktracking search Constraint Loggg gic Programming вЂў A constraint logic program is a logic program that contains constraints in the body of clauses A(X,Y) :-X+Y>0, B(X), C(Y) Constraints are stored in a constraint store Constraint Satisfaction Problems (CSPs) вЂўA state-space search problem where вЂўThe state is defined by n variables V i (i=1,вЂ¦,n) вЂўThe possible values for each variable are from a domain D i вЂўThere are a set of constraints between the variable values вЂўThe goal test checks that all variables have been assigned and no constraints are

5 CONSTRAINT SATISFACTION PROBLEMS In which we see how treating states as more than just little black boxes leads to the invention of a range of powerful new search methods and a deeper understanding of problem structure and complexity. constraint satisfaction problem. вЂў A Constraint Satisfaction Problem consists of 3 components 1. A set of variables. 2. A set of values for each of the variables. 3. A set of constraints between various collections of variables. We must find a value for each of the variables that satisfies all of the constraints.

Full text of the second edition of Artificial Intelligence: foundations of computational agents, Cambridge University Press, 2017 is now available. 4.2.2 Constraint Satisfaction Problems. A constraint satisfaction problem (CSP) consists of a set of variables, Constraint Satisfaction Problems This problem: A binary CSP: вЂў each constraint relates two variables. CIS 391 - Intro to AI 9 Varieties of CSPs Intro to Artificial Intelligence) A1 A3 A2 The image of the same vertex from a different point of view gives a different junction type.

Constraint satisfaction is the group of problems in which finding the solution involves discovering a suitable group of parameters such that the that result falls with some pre-defined boundaries. Many real-world problems can be described as constraint satisfaction problems (CSPs). Researchers in artificial intelligence (AI) usually adopt a constraint satisfaction approach as their preferred method when tackling such problems. However, constraint satisfaction approaches are not widely known amongst operational researchers. The aim of this paper is to introduce constraint satisfaction to the operational researcher.

Sep 05, 2016В В· Constraint satisfaction problems are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations. CSPs represent the entities in a problem as Constraint satisfaction problems (CSPs) вЂў Standard search problem: state is a "black boxвЂњ вЂ“any data structure that supports successor function and goal test вЂў CSP: вЂ“state is defined by variables X i with values from domain D i вЂ“goal test is a set of constraints specifying allowable combinations of values for subsets of variables

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