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Member Since 07 Mar 2002
Offline Last Active Today, 06:15 AM

Posts I've Made

In Topic: how can neural network can be used in videogames

21 May 2016 - 09:01 AM


This is also fun: http://karpathy.github.io/2015/05/21/rnn-effectiveness/

In Topic: how can neural network can be used in videogames

20 May 2016 - 01:51 AM

"You sound like someone that has never programmed either a checkers engine or a chess engine."

You sound like someone who hasn't programmed anything more complex than a "checkers engine or a chess engine".



NNs for basic classification of SIMPLE situational factors are fine, but once the situations are no longer simple (like spotting temporal  cause and effect)  they just dont work too well.

NNs can tell a Siberian Husky from an Alaskan Malamute by looking at their picture. They can translate sentences between any two languages, with very little additional machinery. Certain NNs (LSTMs in particular) can spot temporal relationships extremely well. It just sounds like you made up your mind about what NNs could do a decade ago and your opinion is impervious to new information.


Yeah, Go is actually a very simple game with a very large branching factor. That is NOT the case for most game AI needs.

This is a serious mischaracterization of the difficulties in writing go AI. The 9x9 game has a branching factor comparable to chess, but until a few years ago we couldn't write strong engines even for that version of the game, because the main problem is not the branching factor: It's the lack of a reasonable evaluation function. Now if you look at what AlphaGo has done, one of their key components is what they call their "value network", which is a NN used as an evaluation function. The problem of writing an evaluation function in go is so subtle and so complex that nobody knows any other way of writing a reasonably reliable evaluation function (this is not exactly true: Monte Carlo methods also kind of work for this, and AlphaGo actually blends the two approaches).

Look, I used to be very skeptical of what NNs could do, but they have gotten a lot better. I still don't think they are very useful for game AI, but it's probably a matter of time until they become useful, and it's probably not a waste of your time to learn about them. It seems plausible that, if you can define a reward system in some quantitative and automated way, you can implement good game AI using a utility-based architecture where the sum of future rewards is estimated using a neural network.

In Topic: implementation of neural network

19 May 2016 - 12:03 PM

Consider your inputs to a feed-forward fully-connected neural network as a column vector with real-valued entries. The operation of a typical layer does this

output = non_linearity(matrix * input + biases)

Here `output', `input' and `biases' are column vectors, and `non_linearity' is a function that applies a non-linear transformation to each coordinate in the vector (typically tanh(x) or max(0,x)).

For non-trivial neural networks the bulk of the work comes from the `matrix * input' operation, which can already be parallelized to some extent. However, you get much better parallelism if you compute your network on multiple data samples at the same time (a so-called "minibatch"). It turns out you can just replace the column vectors with matrices, so each column represents a separate data sample from the minibatch, and the formulas are essentially the same. This allows for much more efficient use of parallel hardware, especially if you are using GPUs. All you need to do is use a well-optimized matrix library.

I know nothing about C# or Unity, sorry.

In Topic: how can neural network can be used in videogames

19 May 2016 - 05:15 AM

Checkers as a equivalent to Chess ? ok .........

You sound like someone that has never programmed either a checkers engine or a chess engine. I have done both. And nobody said "equivalent". But they are in the same class.


'Chess' Evaluation function  ( as in 'tool' ??) .... but is it the  fundamental core of the decision logic ?   Which is what Im talking about being a  problematic thing for  NN usage.

Yes, NNs are only a tool. I don't see who you are arguing with here. The main search algorithms to use in boardgames are alpha-beta search and MCTS. Both of them have a two parts that can be implemented using neural networks: An estimate of the probability of each move and an estimate of the result of the game.


'possible'   -- Where AI is concerned I recall that little situation in the 50s where they thought AI was just around the corner, and all kinds of Computer AI goodness was just about solved.   Here we are 60 years later.   'Complexity' has proven to be quite perplexing.

I am not old enough to remember what people were thinking in the 50s. But I know what AlphaGo just did to the game of go using NNs. And it's hard to argue that go is not a complex game.

In Topic: how can neural network can be used in videogames

18 May 2016 - 08:48 AM

I'm not that scared by your FUD about how complex things can get. :)

EDIT - a simple thing to contemplate what Im talking about is --- try to program Chess via a NN based solution.

I already mentioned I have used a NN as evaluation function in checkers. Using one as evaluation function in chess is not [much] harder: http://arxiv.org/abs/1509.01549

Other uses of NNs for chess are possible: http://erikbern.com/2014/11/29/deep-learning-for-chess/