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Much work in computer science has adopted competitive analysis as a tool for decision making under uncertainty. In this work we extend competitive analysis to the context of multi-agent systems. Unlike classical competitive analysis where…

Artificial Intelligence · Computer Science 2007-05-23 Moshe Tennenholtz

Dynamic game theory is an increasingly popular tool for modeling multi-agent, e.g. human-robot, interactions. Game-theoretic models presume that each agent wishes to minimize a private cost function that depends on others' actions. These…

Robotics · Computer Science 2025-10-17 Cade Armstrong , Ryan Park , Xinjie Liu , Kushagra Gupta , David Fridovich-Keil

Rationality is often related to optimal decision making. Humans are known to be bounded rational agents. However, recent advances in computing, and other scientific and technical fields along with large amount of data have led to a feeling…

Computers and Society · Computer Science 2023-06-21 Dibakar Das

In the context of strategic games, we provide an axiomatic proof of the statement Common knowledge of rationality implies that the players will choose only strategies that survive the iterated elimination of strictly dominated strategies.…

Computer Science and Game Theory · Computer Science 2010-06-28 Jonathan A. Zvesper , Krzysztof R. Apt

In this paper the theory of semi-bounded rationality is proposed as an extension of the theory of bounded rationality. In particular, it is proposed that a decision making process involves two components and these are the correlation…

Artificial Intelligence · Computer Science 2013-05-28 Tshilidzi Marwala

Real-life agents seldom have unlimited reasoning power. In this paper, we propose and study a new formal notion of computationally bounded strategic ability in multi-agent systems. The notion characterizes the ability of a set of agents to…

Multiagent Systems · Computer Science 2023-10-27 Catalin Dima , Wojciech Jamroga

In dynamic settings each economic agent's choices can be revealing of her private information. This elicitation via the rationalization of observable behavior depends each agent's perception of which payoff-relevant contingencies other…

Theoretical Economics · Economics 2021-05-17 Evan Piermont , Peio Zuazo-Garin

The concept of rationality is central to the field of artificial intelligence (AI). Whether we are seeking to simulate human reasoning, or trying to achieve bounded optimality, our goal is generally to make artificial agents as rational as…

Artificial Intelligence · Computer Science 2025-09-05 Olivia Macmillan-Scott , Mirco Musolesi

Coalition Logic is a central logic in logical research on strategic reasoning. In a recent paper, Li and Ju argued that generally, models of Coalition Logic, concurrent game models, have three too strong assumptions: seriality, independence…

Computer Science and Game Theory · Computer Science 2025-09-12 Yinfeng Li , Fengkui Ju

From the standpoint of game theory, dominoes is a game that has not received much attention (specially the variety known as draw). It is usually thought that this game is already solved, given general results in game theory. However, the…

Computer Science and Game Theory · Computer Science 2013-10-28 Eduardo Espinosa-Avila , Francisco Hernandez-Quiroz

At the beginning of a dynamic game, players may have exogenous theories about how the opponents are going to play. Suppose that these theories are commonly known. Then, players will refine their first-order beliefs, and challenge their own…

Computer Science and Game Theory · Computer Science 2017-07-28 Emiliano Catonini

Researchers have started using LLM agents in place of human subjects in behavioural and political-science experiments, often as a cheaper substitute for laboratory pools. The substitution does not hold up in strategic settings: humans and…

General Economics · Economics 2026-05-27 Po Han Teo

When humans are subject to an algorithmic decision system, they can strategically adjust their behavior accordingly (``game'' the system). While a growing line of literature on strategic classification has used game-theoretic modeling to…

Machine Learning · Computer Science 2024-10-28 Raman Ebrahimi , Kristen Vaccaro , Parinaz Naghizadeh

We develop a systematic approach to quantum probability as a theory of rational betting in quantum gambles. In these games of chance the agent is betting in advance on the outcomes of several (finitely many) incompatible measurements. One…

Quantum Physics · Physics 2007-05-23 I. Pitowsky

Empirical evidence shows that human behaviour often deviates from game-theoretical rationality. For instance, humans may hold unrealistic expectations about future outcomes. As the evolutionary roots of such biases remain unclear, we…

Multiagent Systems · Computer Science 2025-08-29 Marco Saponara , Elias Fernandez Domingos , Jorge M. Pacheco , Tom Lenaerts

Congestion games model a wide variety of real-world resource congestion problems, such as selfish network routing, traffic route guidance in congested areas, taxi fleet optimization and crowd movement in busy areas. However, existing…

Computer Science and Game Theory · Computer Science 2012-10-19 Asrar Ahmed , Pradeep Varakantham , Shih-Fen Cheng

Bounded rationality, that is, decision-making and planning under resource limitations, is widely regarded as an important open problem in artificial intelligence, reinforcement learning, computational neuroscience and economics. This paper…

Machine Learning · Statistics 2015-12-22 Pedro A. Ortega , Daniel A. Braun , Justin Dyer , Kee-Eung Kim , Naftali Tishby

As we show using the notion of equilibrium in the theory of infinite sequential games, bubbles and escalations are rational for economic and environmental agents, who believe in an infinite world. This goes against a vision of a self…

Computer Science and Game Theory · Computer Science 2013-05-02 Pierre Lescanne

Many applications of intelligent systems require reasoning about the mental states of agents in the domain. We may want to reason about an agent's beliefs, including beliefs about other agents; we may also want to reason about an agent's…

Artificial Intelligence · Computer Science 2013-01-18 Brian Milch , Daphne Koller

Noncooperative games with uncertain payoffs have been classically studied under the expected-utility theory framework, which relies on the strong assumption that agents behave rationally. However, simple experiments on human decision makers…

Computer Science and Game Theory · Computer Science 2025-08-14 Ashok Krishnan K. S. , Hélène Le Cadre , Ana Bušić