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javareinforcement-learningmulti-agent

How do I make a reinforcement learning agent in Java?


I have a challenge that my teacher gave to beat an army of his soldiers on a 18x24 grid, with random obstacles placed on the board. The game is turn based and I have an army of 50 soldiers, each of which needs to either move or attack on their turn.

My problem is I only have access to creating a class of soldiers to fight in this environment. Currently I have a method that evaluates the board position by looking at how many soldiers there are left from each team and does yourTeam - enemyTeam to get the current score, and I have a method that will produce the legal moves for the soldier.

I want to know how I would create a reinforcement learning agent in Java with what I have access to. If you know any ways to do this or any resources that may help that would be great. Thank you for the help!


Solution

  • Java is not a good language for doing math heavy computation (which is what you will need to do for RL). You could attempt to implement the Q-Learning, value-iteration or policy-iteration algorithms but I would avoid doing anything with neural networks/modern deep RL approaches here as your work load will increase dramatically.

    With regard to your problem, if you are to implement one of the old-school algorithms. Think about your state and action space. I have serious concerns about the size of your action space, even with a small number of moves for each solider (say 3 - attack, move up, move down) with 50 soldiers the action space will be very large - 50^3, even this many will be difficult to deal with, any more (even 4 or 5) will send you deep into some complex topics in RL.

    Other problems are - defining a good reward signal, efficiently running (potentially millions) of simulated games.

    The short answer is, this is not something to be taken lightly, it would be challenging and time consuming even for someone who has experience in the field and using Java is a no-no (Python is better). Given you probably don't have long to find a good solution, I would recommend trying a different approach - planning based maybe, or hard coding a reasonable strategy.

    If you still want to go ahead and read up on the topic here are some good resources:

    • Reinforcement Learning an Introduction (Sutton & Barto) - any edition is fine
    • Selected chapters in Artificial Intelligence: A Modern Approach (Russel & Norvig)

    Hope this helps and sorry it may not have been the answer you we hoping for!