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AIMA-Java Core Algorithms from the book Artificial Intelligence a Modern Approach 3rd Ed.
There is a newer version: 3.0.0
package aima.core.search.nondeterministic;

import aima.core.agent.Action;
import aima.core.search.framework.Metrics;
import java.util.Set;

/**
 * Artificial Intelligence A Modern Approach (3rd Edition): Figure 4.11, page
 * 136.

 * 

 * 
 *  * 
 * function AND-OR-GRAPH-SEARCH(problem) returns a conditional plan, or failure
 *   OR-SEARCH(problem.INITIAL-STATE, problem, [])
 * 
 * ---------------------------------------------------------------------------------
 * 
 * function OR-SEARCH(state, problem, path) returns a conditional plan, or failure
 *   if problem.GOAL-TEST(state) then return the empty plan
 *   if state is on path then return failure
 *   for each action in problem.ACTIONS(state) do
 *       plan <- AND-SEARCH(RESULTS(state, action), problem, [state | path])
 *       if plan != failure then return [action | plan]
 *   return failure
 * 
 * ---------------------------------------------------------------------------------
 * 
 * function AND-SEARCH(states, problem, path) returns a conditional plan, or failure
 *   for each s_i in states do
 *      plan_i <- OR-SEARCH(s_i, problem, path)
 *      if plan_i = failure then return failure
 *   return [if s₁ then plan₁ else if s₂ then plan₂ else ... if s_n-1 then plan_n-1 else plan_n]
 * 
 * 
 * 
 * Figure 4.11 An algorithm for searching AND-OR graphs generated by
 * nondeterministic environments. It returns a conditional plan that reaches a
 * goal state in all circumstances. (The notation [x | l] refers to the list
 * formed by adding object x to the front of the list l.)

 * 

 * Note: Unfortunately, this class cannot implement the interface SearchForActions
 * (core.search.framework.SearchForActions) because SearchForActions.search() returns a list of
 * Actions to perform, whereas a nondeterministic search must return a Plan.
 * 
 * @author Andrew Brown
 */
public class AndOrSearch {

	protected int expandedNodes;

	/**
	 * Searches through state space and returns a conditional plan for the given
	 * problem. The conditional plan is a list of either an action or an if-then
	 * construct (consisting of a list of states and consequent actions). The
	 * final product, when printed, resembles the contingency plan on page 134.
	 * 
	 * This function is equivalent to the following on page 136:
	 * 
	 * 	 * 
	 * function AND-OR-GRAPH-SEARCH(problem) returns a conditional plan, or failure
	 *   OR-SEARCH(problem.INITIAL-STATE, problem, [])
	 * 
	 * 
	 * 
	 * @param problem
	 * @return a conditional plan or null on failure
	 */
	public Plan search(NondeterministicProblem problem) {
		this.expandedNodes = 0;
		// OR-SEARCH(problem.INITIAL-STATE, problem, [])
		return this.orSearch(problem.getInitialState(), problem, new Path());
	}

	/**
	 * Returns a conditional plan or null on failure; this function is
	 * equivalent to the following on page 136:
	 * 
	 * 	 * 
	 * function OR-SEARCH(state, problem, path) returns a conditional plan, or failure
	 *   if problem.GOAL-TEST(state) then return the empty plan
	 *   if state is on path then return failure
	 *   for each action in problem.ACTIONS(state) do
	 *       plan <- AND-SEARCH(RESULTS(state, action), problem, [state | path])
	 *       if plan != failure then return [action | plan]
	 *   return failure
	 * 
	 * 
	 * 
	 * @param state
	 * @param problem
	 * @param path
	 * @return a conditional plan or null on failure
	 */
	public Plan orSearch(Object state, NondeterministicProblem problem,
			Path path) {
		// do metrics
		this.expandedNodes++;
		// if problem.GOAL-TEST(state) then return the empty plan
		if (problem.isGoalState(state)) {
			return new Plan();
		}
		// if state is on path then return failure
		if (path.contains(state)) {
			return null;
		}
		// for each action in problem.ACTIONS(state) do
		for (Action action : problem.getActionsFunction().actions(state)) {
			// plan <- AND-SEARCH(RESULTS(state, action), problem, [state|path])
			Plan plan = this.andSearch(
					problem.getResultsFunction().results(state, action),
					problem, path.prepend(state));
			// if plan != failure then return [action|plan]
			if (plan != null) {
				return plan.prepend(action);
			}
		}
		// return failure
		return null;
	}

	/**
	 * Returns a conditional plan or null on failure; this function is
	 * equivalent to the following on page 136:
	 * 
	 * 	 * 
	 * function AND-SEARCH(states, problem, path) returns a conditional plan, or failure
	 *   for each s_i in states do
	 *      plan_i <- OR-SEARCH(s_i, problem, path)
	 *      if plan_i = failure then return failure
	 *   return [if s₁ then plan₁ else if s₂ then plan₂ else ... if s_n-1 then plan_n-1 else plan_n]
	 * 
	 * 
	 * 
	 * @param states
	 * @param problem
	 * @param path
	 * @return a conditional plan or null on failure
	 */
	public Plan andSearch(Set