11 votes
Accepted

Why spend so much time and money to build AIs to play games?

In the book Artificial Intelligence: A Modern Approach (section 5.7, p. 185), Russell and Norvig write In 1965, the Russian mathematician Alexander Kronrod called chess "the Drosophila of ...
9 votes

Is there any board game where a human can still beat an AI?

Not all games (or even board games) are computationally algorithmic. Even the least skilled player is likely to trounce the hottest pattern-matching algorithm in a game of Pictionary (for example). ...
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7 votes

If two perfect chess AI's played each other, would it always be a stalemate or would white win for an inherent first-move advantage?

This relates to the concept of "solved games". In general, two player turn-based games with perfect information - of which chess is an example - can result in all three possible outcomes: a forced win ...
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  • 24.5k
7 votes
Accepted

Is there any board game where a human can still beat an AI?

For many years, the focus has been on games with perfect information. That is, in Chess and Go both of us are looking at the same board. In something like Poker, you have information that I don't have ...
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6 votes
Accepted

What's the optimal policy in the rock-paper-scissors game?

For this, we will need game theory. In game theory, an optimal strategy is one that cannot be exploited by the opponent even if they know your strategy. Let's say you want a strategy where your move ...
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5 votes

What is the difference between game theory and machine learning?

These are big areas, so here is a brief description of the differences: Game theory is concerned with studying solutions for 'games', which are basically a set of decisions leading to certain ...
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  • 5,062
4 votes

Perfect play in information incomplete games

This may be an evolving answer, because the question is, in some sense, a (useful) rabbit hole. I apologize if I don't go deeply into meta-games per se, as it's a little outside of my scope, which is ...
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  • 6,067
4 votes

Is there any flaw to this solution to the One shot prisoner's dilemma

This question is re-inventing the analysis for iterated prisoner's dilemma and the co-evolution that can lead to agents playing super-rationally in the one-shot version, which has been studied really ...
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3 votes

Are perfect and imperfect information games modelled as fully and partially observable environments, respectively?

There is indeed a close parallel here, but the concepts are distinct. Every perfect information game is fully observable, but not every fully observable game is a game of perfect information. A game ...
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3 votes

How to calculate the optimal placements for settlements in Catan without an ML algorithm?

Catan is actually a much more complicated game than the simple rules would suggest, and an exact solution is probably beyond the scope of current AI techniques. Monte Carlo Tree Search or ...
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3 votes
Accepted

How to make minimax optimal?

Minimax deals with two kinds of values: Estimated values determined by a heuristic function. Actual values determined by a terminal state. Commonly, we use the following denotational semantics for ...
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3 votes

Can Alpha–Beta be used on symmetric zero sum games?

If the game is not sequential, there would be no game tree and no need for pruning. Alpha-beta is a technique applied to look-ahead search. Alpha-beta has demonstrated utility in algorithms that ...
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  • 6,067
3 votes
Accepted

Why is tic-tac-toe considered a non-deterministic environment?

The game of TIC-TAC-TOE can be modelled as a non-deterministic Markov decision process (MDP) if, and only if: The opponent is considered part of the environment. This is a reasonable approach when ...
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  • 24.5k
2 votes

Is there any board game where a human can still beat an AI?

Artificially intelligent computer programs should be able to be at the same level or beat humans at every game that we play. This is because games follow rules that are scriptable, and artificial ...
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2 votes

Perfect play in information incomplete games

This second answer attempts to address perfect play in relation to incomplete information specifically. An element in the difficulty in answering this question may be that the concept of perfect play ...
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  • 6,067
2 votes
Accepted

How to define or represent evil in logic

I think you're going to have to be reconciled to the subjective nature of reality. Objectivity is only possible in very special cases such as a Q.E.D. in mathematics, or a solved gamed. Rationality ...
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  • 6,067
2 votes

AI with conflicting objectives?

MOEAs sounds very cool, but I feel that you can't really talk about conflict in AI without discussing generative adversarial networks (GANs), which have been shown to have amazing performance by ...
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2 votes

AI with conflicting objectives?

There are multi-objective optimization problems, where the objective functions may be in conflict with each other, which can potentially have multiple Pareto-optimal solutions. The paper Multi-...
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  • 34.5k
2 votes

How to calculate the optimal placements for settlements in Catan without an ML algorithm?

Historically, the non-ML approach would be an expert system. This is typically a rules-based decision system, falling under the umbrella of symbolic AI. These systems can have strong utility in ...
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  • 6,067
2 votes
Accepted

How can an AI play Flow Free?

A few of us have spent quite a bit of time thinking about this. I summarised our work in a Medium article here: https://towardsdatascience.com/deep-learning-vs-puzzle-games-e996feb76162 Would love to ...
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2 votes

What approaches are there to apply AI to global economic processes?

It's currently just too complex The different sources of information are too varied, in economics this is often referred to as a local knowledge problem, which hampers many large scale plans. Humans ...
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2 votes

What is the difference between genetic algorithms and evolutionary game theory algorithms?

Philip's answer is good, but I'll add to it. In a GA, a population of individuals (typically represented by bit strings) is evaluated for its fitness on a particular task. Each individual is ...
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2 votes
Accepted

Shouldn't the utility function of two-player zero-sum games be in the range $[-1, 1]$?

it can be either. If you consider the lack of reward as "penalty" then getting 0 reward is bad. if you use a value estimator through a neural network, the range of rewards will dictate the squashing ...
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  • 191
1 vote
Accepted

Interesting examples of discrete stochastic games

Some of the domains in the International Probabilistic Planning Competition, such as the Wildlife Preserve benchmark, fit quite well the constraints you have given. Note that the problems are modeled ...
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1 vote

What is the difference between genetic algorithms and evolutionary game theory algorithms?

A genetic algorithm is typically a single population designed to optimise to a specific task, say minimising the distance on the travelling salesman problem. Evolutionary game theory algorithms ...
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  • 221
1 vote

Are perfect and imperfect information games modelled as fully and partially observable environments, respectively?

Not exactly, at least traditionally: in Game Theory, "imperfect information" is most often defined as agents having only partial information about the history of agents' actions, as you correctly ...
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1 vote

Is there a way to predict points on a map?

Leaving aside the time aspect, you could do a cluster analysis on the event coordinates. If you use an algorithm that gives you a medoid (ie centre) of the clusters, you can then look at other points, ...
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  • 5,062
1 vote

How to define or represent evil in logic

After 4 days of research, this is my breakdown of the question: Human uses the term 'Evil' broadly to describe anything that cause sadness or even broadly anything negatively touch the happiness. So ...
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1 vote

How to make minimax optimal?

Short version below. When implementing a minimax algorithm the purpose is usually to find the best possible position of a game board for the player you call max after some amount of moves. In some ...
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