import java.awt.*; import java.io.*; import AgentWorld.*; // The 'main' class for running the 'Agent World' of CS 540 and CS 760. // // - copyrighted 1997, 1998 by Jude Shavlik // (for educational use only) // // YOU SHOULD MAKE YOUR OWN COPY OF THIS FILE AND EDIT IT TO USE // YOUR OWN PLAYER (AS WELL AS YOUR OWN CHOICE OF OTHER PLAYERS). // Be sure (in Unix) to add the following to your ~/.cshrc.local file // in order to have Java find your class files and the AgentWorld package: // // setenv CLASSPATH .:./classes:/p/course/cs540-shavlik/public/AgentWorld/Packages // // On platforms other than the course computers, you'll have to copy // those files over to your machine and make sure these files are in // a classes directory that Java searches. // You can access these class files via // // http://www.cs.wisc.edu/~shavlik/cs540/AgentWorld/Packages // // (this is a WWW link to that /p/course/cs540-shavlik/... directory listed above). public class RunAgentWorld { public static void main(String args[]) { boolean barrenWorld = false; // For debugging purposes, it can be helpful to // set this true and only have your own player // out there. boolean sparseWorld = true; // For slower computers, have less objects // in the world (the dimensions of the // world can't be changed). try { // Need an AgentWindow instance with which to communicate. // This argument indicates whether the game is being displayed. // (you might wish to turn this off in the machine learning HW // to conserve cpu cycles for training). AgentWindow aw = new AgentWindow(true); // Create some 'baby' players that simply do random walks. // Notice you can specify the colors for players, // which will otherwise default depending on the player type. if (!barrenWorld && !sparseWorld) aw.addRandomWalker("Alice", Color.pink); if (!barrenWorld && !sparseWorld) aw.addRandomWalker("Bob", Color.cyan); // Create a malicious player that chases other players. if (!barrenWorld) aw.addAssassin("The Jackal"); // This next player will follow the mouse whenever // the mouse button is down. // (You may wish to only display what this player sees, and then see // how high you can score by guiding it from its perspective. // The ability to maneuver a player is also useful for debugging.) if (!barrenWorld) aw.addFollowMousePlayer("The Pied Piper"); // Here's how you'll hook up your player. // Name your class Player, where is replaced with // you login on the course computers - this will allow us // to mix-and-match players w/o having to worry about name conflicts, // e.g., I'd call mine ShavlikPlayer and create the file ShavlikPlayer.java. // // Below is a sample player that shows how one's code interacts with // the Agent World. You can view this file at // // /p/course/cs760-shavlik/public/AgentWorld/Java/SamplePlayer.java // // or // // http://cs.wisc.edu/~shavlik/cs540/AgentWorld/Java/SamplePlayer.java // // to see how the sensors are read, rewards received, etc. You should // also look at Utils.java in that same directory; it contains some // possibly useful utility functions. // // Also, start with the sensors being displayed (hence, the 'true' // - you'll probably want to delete this 'true' and instead show // the sensors for your OWN agent). if (!barrenWorld) aw.addPlayer(new SamplePlayer(aw, true), "a Sample Player", Color.blue); // Below is how you'll add your own player. Of course, feel // free to change the player's name and color. (When you're // using your own player, you might want to commment-out the // previous command that added the SamplePlayer.) // // aw.addPlayer(new Player(aw, true), // "'s Player", Color.magenta); // The following is a semi-clever, hand-coded player. if (!barrenWorld) aw.addPlayer(new ShavlikPlayer(aw), "a Smart Player", Color.yellow); // The following player has been trained, "from scratch," // using artificial neural networks (ANNs) and a machine learning method // called "reinforcement learning." if (!barrenWorld && !sparseWorld) { String neuralNetworkFileName = "savedShavlikNetwork.jws"; // The above file MUST EXIST IN THE DIRECTORY FROM WHICH YOU INVOKE JAVA // OR OTHERWISE THIS PLAYER WILL NOT BE CREATED. // This design is a bit crude, but it allows for portability. // On the course machines, you can replace the above with the // following full pathname, if you wish: // // /p/course/cs540-shavlik/public/AgentWorld/savedShavlikNetwork.jws // // (Oddity: this works fine in Solaris and WinNT but NOT WIn95???) if (neuralNetworkFileName != null && ((new File(neuralNetworkFileName)).exists())) { aw.addPlayer(new ShavlikANNplayer(aw, neuralNetworkFileName), "ML-Trained Player", Color.orange); } else if (neuralNetworkFileName != null) { Utils.println("The file " + neuralNetworkFileName + " cannot be found."); } } // Add some players whose scores aren't reported on the score board. if (!barrenWorld) { if (sparseWorld) aw.addAnonymousAssassins(1); else aw.addAnonymousAssassins(2); } if (!barrenWorld && !sparseWorld) aw.addAnonymousRandomWalkers(1); if (!barrenWorld && !sparseWorld) aw.addAnonymousSmartPlayers(1); // (Actually, the AnonymousSmartPlayers are more copies of ShavlikPlayer). // Can't have more than 100 of either of the following, // nor more than 25 players. if (!barrenWorld) { if (sparseWorld) aw.addMinerals( 50); else aw.addMinerals(100); } if (!barrenWorld) { if (sparseWorld) aw.addVegetables(50); else aw.addVegetables(100); } // At some point we may try to have a competition among the // players produced by various students. Since the // training and 'testing' environments, should be approximately // equivalent, we'll define the basic initial configuration to have: // // 5 Players (with at least 1 Assassin's & 0 FollowMouse's) // 50 Minerals // 50 Vegetables // // Of course the intelligence of the players will vary from the above // when competing against players of various students. // WE'LL POST MORE INFO ABOUT COMBINING PLAYERS OF MULTIPLE STUDENTS // ON THE CLASS HOME PAGE (http://www.cs.wisc.edu/~shavlik/cs540.html). // The "game manager" sleeps at most this long (in msec) for all the // players to choose their moves. Players that aren't ready continue // in the same direction as their last choice. You may wish to adjust // this depending on the speed of your code/machine and the number of // players. (If all players are ready, the simulator proceeds without // waiting for the duration to expire, so it isn't too harmful to set // this high. However, the player threads seem to occassionally die/hang // for no [obvious] reason; if a player times-out too many times in a row, // its thread will automatically be recreated - a low time-out // causes this detection and restarting to be accomplished faster.) aw.setClockPeriod(150); // You can request that the 'manager' wait for you to // press GO before each move. aw.setSingleStepMode(false); // The default setting is also false. // The following will play the specified number of games, // where each game last for the stated number of steps. // Each game starts in a new randomized initial configuration. // The mean score is reported for each player at the end. // We'll say that games always end after 5000 units of time, // since the optimal behavior depends on game length. // (This command also automatically pushes the Start button.) if (!barrenWorld) aw.playThisManyGamesEachOfThisManyTimeSteps(1000, 5000); // If the above line is commented out, then you can create // the initial configuration before pushing the Start button. } catch(Exception e) { Utils.println("Exception encountered in main method: " + e); Utils.println("The following indicates the location of the problem:"); e.printStackTrace(System.err); Utils.exit(-1); } } }