AI based on Deep Learning

Discussion of all aspects of the game engine, including development of new and existing features.

Moderators: Forum Moderators, Developers

Re: AI based on Deep Learning

Postby mattsc » December 19th, 2017, 12:53 am

milwac wrote:This is an excellent resource mattsc, thank you! While I look through this code, perhaps I can be a bit more specific about what I'm looking for right now, and ask : are there some simple functions that I can write in a script in Python or Lua to access in game properties like - side to move, villages each side has, types of units available, positions of units, reachable hexes for a unit etc.? I wish to visualize these properties while a game/replay is being played, and see which ones could be useful as input features, before I think about the AI code itself.

I don't know about python, but a lot of this is built-in Wesnoth Lua functionality. Go to LuaWML and check out the links in Section 4. For example:

- side to move: wesnoth.current.side
- villages: wesnoth.get_villages
- types of units: wesnoth.unit_types
- reachable hexes: wesnoth.find_reach

If you want more complex functions, there's a good chance that I or somebody else has already written something in our own AI experiments. Just ask, it might exist. These are very different types of AI though, so likely not much help to what you want to do otherwise.

The bigger problem I see is that you say you want to visualize this while you are playing a replay. The way Wesnoth works is that anything you want to see in a replay needs to be there while the game is being "recorded" (played). So while that is possible (some of my AIs have that type of debugging mechanism built in; see, for example, eval_exec_CA.lua), it has to be present when the game is started and cannot be applied after the fact to previous replays. Well, it is possible, but you would have to add it by editing the replay files. Writing a script to do so automatically is, of course, a possibility.
Posts: 991
Joined: October 13th, 2010, 6:14 pm
Location: Wandering, mostly aimlessly

Re: AI based on Deep Learning

Postby milwac » January 2nd, 2018, 2:03 pm

Thanks mattsc for all your help (on this thread and offline) in understanding how a new AI can be written in Wesnoth and how the AI functions in general.

So far I have come to the conclusion that simulating a sequence of moves (in a single turn or otherwise) is not possible with the current AI framework provided in Lua. It is only possible to evaluate the current state of the game and perform some actions (moves) on it, but it is not possible to copy over the current state, perform actions on that state, evaluate the final modified state and then perform the actual actions on the original state. This process is essential for any learning algorithm to work, in fact, it is essential for any algorithm which tries to 'look ahead' for instance, minimax. It is also essential to perform any sort of optimization algorithm to optimize actions of a single turn (recruitment or unit placement).

This has been my observation. mattsc did suggest to me in a pm that it might be possible to write a wrapper around the evaluation and execution functions of the candidate actions, and call them.. but i wonder if there is a possibility to save a copy of the game state and run these wrapper functions on that copy, in such a way that the standard wesnoth.<xyz> queries can be made on the copy. So far, I think not.

If someone thinks that there is a way to perform simulations like the way I want, please do let me know.

User avatar
Posts: 27
Joined: April 9th, 2010, 11:40 am


Return to Coder’s Corner

Who is online

Users browsing this forum: No registered users and 1 guest