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Related papers: Derandomization in Game-theoretic Probability

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We give elementary examples within a framework for studying decisions under uncertainty where probabilities are only roughly known. The framework, in gambling terms, is that the size of a bet is proportional to the gambler's perceived…

Probability · Mathematics 2023-12-19 David J. Aldous , F. Thomas Bruss

We consider how an agent should update her uncertainty when it is represented by a set P of probability distributions and the agent observes that a random variable X takes on value x, given that the agent makes decisions using the minimax…

Artificial Intelligence · Computer Science 2014-07-29 Peter D. Grunwald , Joseph Y. Halpern

A generalized model of games is proposed, in which cooperative games and non-cooperative games are special cases. Some games that are neither cooperative nor non-cooperative can be expressed and analyzed. The model is based on relationships…

Computer Science and Game Theory · Computer Science 2016-10-10 Jiawei Li

We compare games under delayed control and delay games, two types of infinite games modelling asynchronicity in reactive synthesis. In games under delayed control both players suffer from partial informedness due to symmetrically delayed…

Computer Science and Game Theory · Computer Science 2025-03-19 Martin Fränzle , Paul Kröger , Sarah Winter , Martin Zimmermann

We study a multi-agent decision problem in population games, where agents select from multiple available strategies and continually revise their selections based on the payoffs associated with these strategies. Unlike conventional…

Multiagent Systems · Computer Science 2024-09-17 Shinkyu Park

A game-theoretic setting provides a mathematical basis for analysis of strategic interaction among competing agents and provides insights into both classical and quantum decision theory and questions of strategic choice. An outstanding…

Quantum Physics · Physics 2018-07-24 Azhar Iqbal , James M. Chappell , Derek Abbott

Planning safe robot motions in the presence of humans requires reliable forecasts of future human motion. However, simply predicting the most likely motion from prior interactions does not guarantee safety. Such forecasts fail to model the…

Artificial Intelligence · Computer Science 2023-10-23 Kushal Kedia , Prithwish Dan , Sanjiban Choudhury

Evolution of distribution of strategies in game theory is an interesting question that has been studied only for specific cases. Here I develop a general method to extend analysis of the evolution of continuous strategy distributions given…

Populations and Evolution · Quantitative Biology 2020-03-16 Georgiy Karev

A new class of stochastic variables, governed by a specifice set of rules, is introduced. These rules force them to loose some properties usually assumed for this kind of variables. We demonstrate that stochastic processes driven by these…

Quantum Physics · Physics 2007-05-23 J. M. A. Figueiredo

In game theory, players have continuous expected payoff functions and can use fixed point theorems to locate equilibria. This optimization method requires that players adopt a particular type of probability measure space. Here, we introduce…

Optimization and Control · Mathematics 2007-05-23 Michael J. Gagen , Kae Nemoto

We study the game of go from a complex network perspective. We construct a directed network using a suitable definition of tactical moves including local patterns, and study this network for different datasets of professional tournaments…

Computer Science and Game Theory · Computer Science 2012-04-20 Bertrand Georgeot , Olivier Giraud

A method for computing probabilistic propositions is presented. It assumes the availability of a single external routine for computing the probability of one instantiated variable, given a conjunction of other instantiated variables. In…

Artificial Intelligence · Computer Science 2013-04-11 Gregory F. Cooper

The paper introduces a new approach to theory of differential games in which entangled players try to predict and influence actions of their adversaries. The entanglement is generated be a joint probability density known by the players.…

General Physics · Physics 2012-09-03 Michail Zak

Deep reinforcement learning is an increasingly popular technique for synthesising policies to control an agent's interaction with its environment. There is also growing interest in formally verifying that such policies are correct and…

Artificial Intelligence · Computer Science 2022-06-02 Edoardo Bacci , David Parker

We extend the open games framework for compositional game theory to encompass also mixed strategies, making essential use of the discrete probability distribution monad. We show that the resulting games form a symmetric monoidal category,…

Logic in Computer Science · Computer Science 2020-09-16 Neil Ghani , Clemens Kupke , Alasdair Lambert , Fredrik Nordvall Forsberg

We use a probabilistic method to produce some combinatorial inequalities by considering pattern containment in permutations and words.

Combinatorics · Mathematics 2007-05-23 Alexander I. Burstein

We present a general theorem for distributed synthesis problems in coordination games with $\omega$-regular objectives of the form: If there exists a winning strategy for the coalition, then there exists an "essential" winning strategy,…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-04-27 Dietmar Berwanger , Anup Basil Mathew , R. Ramanujam

Random number generators are widely used in practical algorithms. Examples include simulation, number theory (primality testing and integer factorization), fault tolerance, routing, cryptography, optimization by simulated annealing, and…

Data Structures and Algorithms · Computer Science 2010-04-21 Richard P. Brent

Traffic scenarios are inherently interactive. Multiple decision-makers predict the actions of others and choose strategies that maximize their rewards. We view these interactions from the perspective of game theory which introduces various…

Machine Learning · Computer Science 2020-04-28 Christian Muench , Frans A. Oliehoek , Dariu M. Gavrila

The recognition of the agency of the knower has enormously enriched our understanding of knowledge production. There is a growing realization that what we know about how we know affects our interpretation of reality. This realization…

History and Philosophy of Physics · Physics 2011-04-22 Gennady Shkliarevsky