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AIMA-Java Core Algorithms from the book Artificial Intelligence a Modern Approach 3rd Ed.

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package aima.core.search.csp;

import aima.core.util.datastructure.FIFOQueue;

/**
 * 
 * Artificial Intelligence A Modern Approach (3rd Ed.): Figure 6.3, Page 209.
*
* *
 * 
 * function AC-3(csp) returns false if an inconsistency is found and true otherwise
 *    inputs: csp, a binary CSP with components (X, D, C)
 *    local variables: queue, a queue of arcs, initially all the arcs in csp
 *    while queue is not empty do
 *       (Xi, Xj) = REMOVE-FIRST(queue)
 *       if REVISE(csp, Xi, Xj) then
 *          if size of Di = 0 then return false
 *             for each Xk in Xi.NEIGHBORS - {Xj} do
 *                add (Xk, Xi) to queue
 *    return true
 * 
 * function REVISE(csp, Xi, Xj) returns true iff we revise the domain of Xi
 *    revised = false
 *    for each x in Di do
 *       if no value y in Dj allows (x ,y) to satisfy the constraint between Xi and Xj then
 *          delete x from Di
 *          revised = true
 *    return revised
 * 
 * 
* * Figure 6.3 The arc-consistency algorithm AC-3. After applying AC-3, either * every arc is arc-consistent, or some variable has an empty domain, indicating * that the CSP cannot be solved. The name "AC-3" was used by the algorithm's * inventor (Mackworth, 1977) because it's the third version developed in the * paper. * * @author Ruediger Lunde */ public class AC3Strategy { /** * Makes a CSP consisting of binary constraints arc-consistent. * * @return An object which indicates success/failure and contains data to * undo the operation. */ public DomainRestoreInfo reduceDomains(CSP csp) { DomainRestoreInfo result = new DomainRestoreInfo(); FIFOQueue queue = new FIFOQueue(); for (Variable var : csp.getVariables()) queue.add(var); reduceDomains(queue, csp, result); return result.compactify(); } /** * Reduces the domain of the specified variable to the specified value and * reestablishes arc-consistency. It is assumed that the provided CSP is * arc-consistent before the call. * * @return An object which indicates success/failure and contains data to * undo the operation. */ public DomainRestoreInfo reduceDomains(Variable var, Object value, CSP csp) { DomainRestoreInfo result = new DomainRestoreInfo(); Domain domain = csp.getDomain(var); if (domain.contains(value)) { if (domain.size() > 1) { FIFOQueue queue = new FIFOQueue(); queue.add(var); result.storeDomainFor(var, domain); csp.setDomain(var, new Domain(new Object[] { value })); reduceDomains(queue, csp, result); } } else { result.setEmptyDomainFound(true); } return result.compactify(); } private void reduceDomains(FIFOQueue queue, CSP csp, DomainRestoreInfo info) { while (!queue.isEmpty()) { Variable var = queue.pop(); for (Constraint constraint : csp.getConstraints(var)) { if (constraint.getScope().size() == 2) { Variable neighbor = csp.getNeighbor(var, constraint); if (revise(neighbor, var, constraint, csp, info)) { if (csp.getDomain(neighbor).isEmpty()) { info.setEmptyDomainFound(true); return; } queue.push(neighbor); } } } } } private boolean revise(Variable xi, Variable xj, Constraint constraint, CSP csp, DomainRestoreInfo info) { boolean revised = false; Assignment assignment = new Assignment(); for (Object iValue : csp.getDomain(xi)) { assignment.setAssignment(xi, iValue); boolean consistentExtensionFound = false; for (Object jValue : csp.getDomain(xj)) { assignment.setAssignment(xj, jValue); if (constraint.isSatisfiedWith(assignment)) { consistentExtensionFound = true; break; } } if (!consistentExtensionFound) { info.storeDomainFor(xi, csp.getDomain(xi)); csp.removeValueFromDomain(xi, iValue); revised = true; } } return revised; } }




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