7 votes
Accepted

Why most imperfect information games usually use non machine learning AI?

A heuristic search using MCTS + minimax + alphabeta pruning is a highly efficient AI planning process. What the AI techniques of reinforcement learning (RL) plus neural networks (NNs) typically add to ...
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  • 23.9k
4 votes

Is a good evaluation function as good as any of the extensions of alpha-beta pruning?

To build on Neil's answer a bit, you're right that the better your evaluation function gets, the less work your optimization function will need to perform. If your evaluation function gets good enough,...
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3 votes
Accepted

Is it standard to say that an evaluation function estimates the “goodness” of a position?

Yes, "goodness" is a common description of the value generated by an evaluation function. For example, "Artificial Intelligence" p. 77; "Knowledge-Free and Learning-Based Methods in Intelligent Game ...
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3 votes

Can games be solved without an evaluation function?

Human chess and go experts clearly use evaluation functions. They do come up with moves that look sensible without evaluating the board position, but to validate these candidate moves they evaluate ...
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2 votes

Is a good evaluation function as good as any of the extensions of alpha-beta pruning?

A perfect evaluation function would mean that you only had to do a local search - i.e. maximise over next set of decisions - in order for an agent to behave optimally in an environment. As such if ...
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2 votes

Game AI evaluation function and making progress towards winning

What I'm missing here is a way to direct the evaluation function to actually winning. For example, a perfect evaluation function for a won position in chess would always return ...
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  • 9,379
2 votes
Accepted

What is the difference between the heuristic function and the evaluation function in A*?

What is the difference between the heuristic function and the evaluation function in A*? The evaluation function, often denoted as $f$, is the function that you use to choose which node to expand ...
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  • 33.8k
1 vote

What inherent quality of a function makes it treated as either loss or evaluation metric?

Common loss functions, like the cross-entropy or mean squared error, are chosen because, if you minimize them, you are actually maximizing the likelihood of the parameters given the observed data. In ...
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1 vote

How do I write a good evaluation function for a board game?

Based on your description, I'd maximize the following terms: i -max(f - 10 - (MAX_FIELD_INDEX - i), 0) - assuming consumption ...
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1 vote

How to design a good evaluation function for a go-like game?

If you have the best combination of distance between the stones, you should choose the best move to win. In this case, you have to be close to where your opponent plays. It is best to do this by ...
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