8
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 ...
- 32.9k
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,...
- 9,342
3
votes
why cross entropy loss has to be multiplied by a batch size during an evaluation in transformer model?
That is because the default reduction for the CEP loss calculation is mean. Hence to find the true average across all batches, you first multiply by the batch size and then divide by total number of ...
- 31
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 ...
- 146
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 ...
- 4,295
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 ...
- 32.9k
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 ...
- 10.4k
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 ...
- 41.1k
1
vote
Can we achieve optimality with minimax using an evaluation function?
You can take any two player zero-sum game and change its rules, so that they become:
Start from the game state being evaluated.
Play for up to N turns.
If no winner is found after N turns, the winner ...
- 32.9k
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 ...
- 41.1k
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 ...
- 563
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 ...
- 21
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