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In this paper, I will demonstrate a new perspective on the Two Envelope Problem. I hope to show with convincing clarity how the paradox results from an inherent problem pertaining to the interpretation of Bayesian probability. Specifically,…

Other Statistics · Statistics 2012-08-27 Eric Bliss

Parrondo's paradox is about a paradoxical game and gambling where two probabilistic losing games can be combined to form a winning game. While the counter intuitive game is interesting in itself, it can be thought of a discrete version of…

Physics and Society · Physics 2016-02-16 Abhijit Kar Gupta , Sourabh Banerjee

We study a simple example of a sequential game illustrating problems connected with making rational decisions that are universal for social sciences. The set of chooser's optimal decisions that manifest his preferences in case of a constant…

Physics and Society · Physics 2007-05-23 Edward W. Piotrowski , Marcin Makowski

In many social dilemmas, individuals tend to generate a situation with low payoffs instead of a system optimum ("tragedy of the commons"). Is the routing of traffic a similar problem? In order to address this question, we present…

Physics and Society · Physics 2007-05-23 Dirk Helbing , Martin Schonhof , Hans-Ulrich Stark , Janusz A. Holyst

Parrondo's paradox arises in sequences of games in which a winning expectation may be obtained by playing the games in a random order, even though each game in the sequence may be lost when played individually. We present a suitable version…

Probability · Mathematics 2007-06-19 Antonio Di Crescenzo

The combination of the Bayesian game and learning has a rich history, with the idea of controlling a single agent in a system composed of multiple agents with unknown behaviors given a set of types, each specifying a possible behavior for…

Machine Learning · Computer Science 2024-11-21 Tongxin Li , Tinashe Handina , Shaolei Ren , Adam Wierman

In this paper I present an argument and a general schema which can be used to construct a problem case for any decision theory, in a way that could be taken to show that one cannot formulate a decision theory that is never outperformed by…

Artificial Intelligence · Computer Science 2021-01-05 Joar Skalse

Decision-making AI agents are often faced with two important challenges: the depth of the planning horizon, and the branching factor due to having many choices. Hierarchical reinforcement learning methods aim to solve the first problem, by…

Machine Learning · Computer Science 2022-01-25 Andrei Nica , Khimya Khetarpal , Doina Precup

We describe and develop a close relationship between two problems that have customarily been regarded as distinct: that of maximizing entropy, and that of minimizing worst-case expected loss. Using a formulation grounded in the equilibrium…

Statistics Theory · Mathematics 2007-06-13 Peter D. Grunwald , A. Philip Dawid

Decomposition methods are often used for producing counterfactual predictions in non-strategic settings. When the outcome of interest arises from a game-theoretic setting where agents are better off by deviating from their strategies after…

Econometrics · Economics 2024-07-03 Nathan Canen , Kyungchul Song

Recently, Apt and Markakis introduced a model for product adoption in social networks with multiple products, where the agents, influenced by their neighbours, can adopt one out of several alternatives (products). To analyze these networks…

Computer Science and Game Theory · Computer Science 2013-07-18 Krzysztof R. Apt , Sunil Simon

We introduce a dataset of natural-language questions in the decision theory of so-called Newcomb-like problems. Newcomb-like problems include, for instance, decision problems in which an agent interacts with a similar other agent, and thus…

Computation and Language · Computer Science 2025-06-17 Caspar Oesterheld , Emery Cooper , Miles Kodama , Linh Chi Nguyen , Ethan Perez

AI systems increasingly support human decision-making. In many cases, despite the algorithm's superior performance, the final decision remains in human hands. For example, an AI may assist doctors in determining which diagnostic tests to…

Artificial Intelligence · Computer Science 2026-02-20 Gali Noti , Kate Donahue , Jon Kleinberg , Sigal Oren

There is a common belief that humans and many animals follow transitive inference (choosing A over C on the basis of knowing that A is better than B and B is better than C). Transitivity seems to be the essence of rational choice. We…

Computer Science and Game Theory · Computer Science 2014-09-23 Marcin Makowski , Edward W. Piotrowski

Motivated by the fact that the same social dilemma can be perceived differently by different players, we here study evolutionary multigames in structured populations. While the core game is the weak prisoner's dilemma, a fraction of the…

Physics and Society · Physics 2014-10-10 Zhen Wang , Attila Szolnoki , Matjaz Perc

A striking limitation of human cognition is our inability to execute some tasks simultaneously. Recent work suggests that such limitations can arise from a fundamental tradeoff in network architectures that is driven by the sharing of…

Neurons and Cognition · Quantitative Biology 2020-07-08 Yotam Sagiv , Sebastian Musslick , Yael Niv , Jonathan D. Cohen

The transitivity of preferences is one of the basic assumptions used in the theory of games and decisions. It is often equated with rationality of choice and is considered useful in building rankings. Intransitive preferences are considered…

Quantum Physics · Physics 2015-06-23 Marcin Makowski , Edward W. Piotrowski , Jan Sładkowski

This paper examines the integration of computational complexity into game theoretic models. The example focused on is the Prisoner's Dilemma, repeated for a finite length of time. We show that a minimal bound on the players' computational…

Computer Science and Game Theory · Computer Science 2007-05-23 Yishay Mor , Jeffrey S. Rosenschein

The famous Saint Petersburg Paradox (St. Petersburg Paradox) shows that the theory of expected value does not capture the real-world economics of decision-making problems. Over the years, many economic theories were developed to resolve the…

General Economics · Economics 2020-05-19 Daniel Muller , Tshilidzi Marwala

There has been a flurry of research in recent years on notions of fairness in ranking and recommender systems, particularly on how to evaluate if a recommender allocates exposure equally across groups of relevant items (also known as…

Information Retrieval · Computer Science 2022-10-17 Flavien Prost , Ben Packer , Jilin Chen , Li Wei , Pierre Kremp , Nicholas Blumm , Susan Wang , Tulsee Doshi , Tonia Osadebe , Lukasz Heldt , Ed H. Chi , Alex Beutel