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2226

Dominion Isotropic / Re: Decline of civility on isotropic?

« on: February 08, 2012, 04:18:58 am »

I'm fairly new to isotropic and generally I've had really good luck with civility, especially compared to a lot of other online games (where people are mostly assholes). In fact, lots of people are willing to discuss strategy after games, sometimes even if they lost, which is really nice for improving when they are a high-level player.

The worst incivility I've encountered so far was after some KC-Swindler shenanigans. (To be fair, that's about as rage-inducing as anything in Dominion.)

18:45 Bengoshi: man, has anyone ever told you that you are a jackass who dserves to be shot at close range in the head?

2227

Simulation / Re: Simulation Challenge - Endgame Polish

« on: January 21, 2012, 05:18:25 pm »

I was thinking the best way to play the endgame is to just run a minmax search over the next N turns and use the result of that to guide your decision. Of course, you can't do that with just XML.

A straightforward minimax approach will run into a couple problems:

1. Randomness & imperfect information. These are just plain difficult to handle in minimax. My guess is that the best way to deal with this is to pretend that players draw randomly from their decks at the beginning of their turns (rather than shuffling and then drawing from the top during their clean-up phases) and also require that players show all their treasure in hand when playing, even though that's not required by the rules, since that's usually how people play on isotropic.

By doing this, the game becomes perfect information and the randomness is spread out a bit. But you're still going to have huge branching factors from the random draws and I believe the randomness will prevent use of alphabeta pruning--both of these factors limit your search depth a lot.

One nice aspect of big money is that the number of possible states is a bit restricted, so you might be able to get some mileage out of combining duplicate states.

2. What's your evaluation function? It can't be VPs because the shallow search (because of problem #1) might cause the bot to start preparing for greening too early. Any other hand-coded evaluation function is going to introduce human opinions about strategy, and avoiding those was the point of resorting to minimax in the first place. I imagine the right way to go here might be Monte Carlo evaluation (like what's used for Go) or machine learning (like what's used for Backgammon).