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The Brown-UMBC Reinforcement Learning and Planning (BURLAP) Java code library is for the use and development of single or multi-agent planning and learning algorithms and domains to accompany them. The library uses a highly flexible state/observation representation where you define states with your own Java classes, enabling support for domains that discrete, continuous, relational, or anything else. Planning and learning algorithms range from classic forward search planning to value-function-based stochastic planning and learning algorithms.

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package burlap.shell.command.env;

import burlap.mdp.core.Domain;
import burlap.mdp.core.state.State;
import burlap.mdp.core.oo.OODomain;
import burlap.mdp.core.oo.state.MutableOOState;
import burlap.mdp.core.oo.state.ObjectInstance;
import burlap.mdp.singleagent.environment.Environment;
import burlap.mdp.singleagent.environment.extensions.EnvironmentDelegation;
import burlap.mdp.singleagent.environment.extensions.StateSettableEnvironment;
import burlap.shell.BurlapShell;
import burlap.shell.EnvironmentShell;
import burlap.shell.command.ShellCommand;
import joptsimple.OptionParser;
import joptsimple.OptionSet;

import java.io.PrintStream;
import java.util.List;
import java.util.Scanner;

/**
 * A {@link burlap.shell.command.ShellCommand} for adding an OO-MDP object to the current {@link burlap.mdp.singleagent.environment.Environment}
 * {@link State}. Use the -h option for help information.
 * @author James MacGlashan.
 */
public class AddStateObjectCommand implements ShellCommand {

	protected OptionParser parser = new OptionParser("vh*");
	protected OODomain domain = null;

	public AddStateObjectCommand(Domain domain) {
		if(domain instanceof OODomain) {
			this.domain = (OODomain) domain;
		}
	}

	@Override
	public String commandName() {
		return "addOb";
	}

	@Override
	public int call(BurlapShell shell, String argString, Scanner is, PrintStream os) {
		Environment env = ((EnvironmentShell)shell).getEnv();
		OptionSet oset = this.parser.parse(argString.split(" "));
		List args = (List)oset.nonOptionArguments();
		if(oset.has("h")){
			os.println("[-v] objectClass objectName\nAdds an OO-MDP object instance of class objectClass and with name " +
					"objectName to the current state of the environment. The environment must implement StateSettableEnvironment " +
					"for this operation to work. The Java ObjectInstance implementation used will be MutableObjectInstance.\n\n" +
					"-v print the new Environment state after completion.");
			return 0;
		}

		StateSettableEnvironment senv = (StateSettableEnvironment) EnvironmentDelegation.Helper.getDelegateImplementing(env, StateSettableEnvironment.class);
		if(senv == null){
			os.println("Cannot add object to environment state, because the environment does not implement StateSettableEnvironment");
			return 0;
		}

		if(args.size() != 2){
			return -1;
		}

		if(domain == null){
			os.println("Cannot add object to state, because input domain is not an OODomain");
			return 0;
		}

		Class oclass = domain.stateClass(args.get(0));
		if(oclass == null){
			os.println("Cannot add object to state, because the domain does not know about any OO-MDP object class named " + args.get(0));
		}


		ObjectInstance o = null;
		try {
			o = (ObjectInstance)oclass.newInstance();
			o = o.copyWithName(args.get(1));
		} catch(InstantiationException e) {
			return 0;
		} catch(IllegalAccessException e) {
			return 0;
		}

		State s = env.currentObservation();

		if(!(s instanceof MutableOOState)){
			os.println("Cannot add object to state, because the state of the environment does not implement MutableOOState");
		}

		((MutableOOState)s).addObject(o);
		senv.setCurStateTo(s);

		if(oset.has("v")){
			os.println(senv.currentObservation().toString());
		}

		return 1;
	}
}