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We study a generalization of the Mermin-Peres magic square game to arbitrary rectangular dimensions. After exhibiting some general properties, these rectangular games are fully characterized in terms of their optimal win probabilities for…

Quantum Physics · Physics 2020-12-11 Sean A. Adamson , Petros Wallden

It is shown that under reasonable assumptions a Drake-style equation can be obtained for the probability that our universe is the result of a deliberate simulation. Evaluating loose bounds for certain terms in the equation shows that the…

Popular Physics · Physics 2021-03-23 Alexandre Bibeau-Delisle , Gilles Brassard

A long-standing open problem in algorithmic game theory asks whether or not there is a polynomial time algorithm to compute a Nash equilibrium in a random bimatrix game. We study random win-lose games, where the entries of the $n\times n$…

Computer Science and Game Theory · Computer Science 2025-10-16 Andrea Collevecchio , Gabor Lugosi , Adrian Vetta , Rui-Ray Zhang

Consider QBF, the Quantified Boolean Formula problem, as a combinatorial game ruleset. The problem is rephrased as determining the winner of the game where two opposing players take turns assigning values to boolean variables. In this…

Computational Complexity · Computer Science 2014-12-31 Kyle Burke

There seems to be an upper limit to predicting the outcome of matches in (semi-)professional sports. Recent work has proposed that this is due to chance and attempts have been made to simulate the distribution of win percentages to identify…

Applications · Statistics 2015-08-21 Albrecht Zimmermann

We study the termination problem for probabilistic term rewrite systems. We prove that the interpretation method is sound and complete for a strengthening of positive almost sure termination, when abstract reduction systems and term rewrite…

Symbolic Computation · Computer Science 2018-02-28 Martin Avanzini , Ugo Dal Lago , Akihisa Yamada

We consider extensive form win-lose games over a complete binary-tree of depth $n$ where players act in an alternating manner. We study arguably the simplest random structure of payoffs over such games where 0/1 payoffs in the leafs are…

Computer Science and Game Theory · Computer Science 2019-09-11 Urban Larsson , Yakov Babichenko

Computing equilibria of games is a central task in computer science. A large number of results are known for \emph{Nash equilibrium} (NE). However, these can be adopted only when coalitions are not an issue. When instead agents can form…

Computer Science and Game Theory · Computer Science 2017-11-20 Nicola Gatti , Marco Rocco , Tuomas Sandholm

The Possible-Winner problem asks, given an election where the voters' preferences over the set of candidates is partially specified, whether a distinguished candidate can become a winner. In this work, we consider the computational…

Computer Science and Game Theory · Computer Science 2018-02-27 Batya Kenig

In a guessing game, players guess the value of a random real number selected using some probability density function. The winner may be determined in various ways; for example, a winner can be a player whose guess is closest in magnitude to…

Computer Science and Game Theory · Computer Science 2016-07-11 Anthony Mendes , Kent E. Morrison

Games on recursive game graphs can be used to reason about the control flow of sequential programs with recursion. In games over recursive game graphs, the most natural notion of strategy is the modular strategy, i.e., a strategy that is…

Logic in Computer Science · Computer Science 2014-08-27 Ilaria De Crescenzo , Salvatore La Torre , Yaron Velner

Probability estimation models play an important role in various fields, such as weather forecasting, recommendation systems, and sports analysis. Among several models estimating probabilities, it is difficult to evaluate which model gives…

Machine Learning · Computer Science 2024-06-06 Euihyeon Choi , Jooyoung Kim , Wonkyung Lee

In probabilistic programming, the inference problem asks to determine a program's posterior distribution conditioned on its "observe" instructions. Inference is challenging, especially when exact rather than approximate results are…

Formal Languages and Automata Theory · Computer Science 2025-11-26 Dominik Geißler , Tobias Winkler

We introduce a "high probability" framework for repeated games with incomplete information. In our non-equilibrium setting, players aim to guarantee a certain payoff with high probability, rather than in expected value. We provide a high…

Computer Science and Game Theory · Computer Science 2015-09-30 Payam Delgosha , Amin Gohari , Mohammad Akbarpour

We present two variants of a multi-agent reinforcement learning algorithm based on evolutionary game theoretic considerations. The intentional simplicity of one variant enables us to prove results on its relationship to a system of ordinary…

Machine Learning · Computer Science 2024-05-29 Johann Bauer , Sheldon West , Eduardo Alonso , Mark Broom

The aim of this paper is to study the asymptotic behavior of strongly reinforced interacting urns with partial memory sharing. The reinforcement mechanism considered is as follows: draw at each step and for each urn a white or black ball…

Probability · Mathematics 2012-01-10 Mickaël Launay

We investigate uniformity properties of strategies. These properties involve sets of plays in order to express useful constraints on strategies that are not \mu-calculus definable. Typically, we can state that a strategy is…

Computer Science and Game Theory · Computer Science 2013-03-05 Bastien Maubert , Sophie Pinchinat , Laura Bozzelli

In strategy games, one of the most important aspects of game design is maintaining a sense of challenge for players. Many mobile titles feature quick gameplay loops that allow players to progress steadily, requiring an abundance of levels…

Machine Learning · Computer Science 2024-06-13 Joakim Bergdahl , Alessandro Sestini , Linus Gisslén

A commonly used heuristic in RL is experience replay (e.g.~\citet{lin1993reinforcement, mnih2015human}), in which a learner stores and re-uses past trajectories as if they were sampled online. In this work, we initiate a rigorous study of…

Machine Learning · Computer Science 2021-12-09 Liran Szlak , Ohad Shamir

In adversarial environments, one side could gain an advantage by identifying the opponent's strategy. For example, in combat games, if an opponents strategy is identified as overly aggressive, one could lay a trap that exploits the…

Machine Learning · Computer Science 2021-08-03 Mark Rucker , Stephen Adams , Roy Hayes , Peter A. Beling
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