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It is frequently suggested that predictions made by game theory could be improved by considering computational restrictions when modeling agents. Under the supposition that players in a game may desire to balance maximization of payoff with…

Computer Science and Game Theory · Computer Science 2015-03-13 Hubie Chen

We introduce a class of extensive form games where players might not be able to foresee the possible consequences of their decisions and form a model of their opponents which they exploit to achieve a more profitable outcome. We improve…

Artificial Intelligence · Computer Science 2016-05-31 Paolo Turrini

We construct several definitions of imbalance and playability, both of which are related to the existence of dominated strategies. Specifically, a maximally balanced game and a playable game cannot have dominated strategies for any player.…

General Economics · Economics 2025-11-07 Itai Maimon

Driven by recent successes in two-player, zero-sum game solving and playing, artificial intelligence work on games has increasingly focused on algorithms that produce equilibrium-based strategies. However, this approach has been less…

Computer Science and Game Theory · Computer Science 2022-06-24 Dustin Morrill , Ryan D'Orazio , Reca Sarfati , Marc Lanctot , James R. Wright , Amy Greenwald , Michael Bowling

A growing line of work has investigated the development of neural NLP models that can produce rationales--subsets of input that can explain their model predictions. In this paper, we ask whether such rationale models can also provide…

Computation and Language · Computer Science 2022-05-05 Howard Chen , Jacqueline He , Karthik Narasimhan , Danqi Chen

Consider a game where Alice generates an integer and Bob wins if he can factor that integer. Traditional game theory tells us that Bob will always win this game even though in practice Alice will win given our usual assumptions about the…

Computer Science and Game Theory · Computer Science 2009-11-18 Lance Fortnow , Rahul Santhanam

Iterated admissibility (IA) can be seen as exhibiting a minimal criterion of rationality in games. In order to make this intuition more precise, the epistemic characterization of this game-theoretic solution has been actively investigated…

Logic · Mathematics 2013-04-19 Fernando Tohmè , Gianluca Caterina , Rocco Gangle

With recent advances in natural language processing, rationalization becomes an essential self-explaining diagram to disentangle the black box by selecting a subset of input texts to account for the major variation in prediction. Yet,…

Machine Learning · Computer Science 2023-09-12 Wenbo Zhang , Tong Wu , Yunlong Wang , Yong Cai , Hengrui Cai

We investigate multi-round team competitions between two teams, where each team selects one of its players simultaneously in each round and each player can play at most once. The competition defines an extensive-form game with perfect…

Computer Science and Game Theory · Computer Science 2016-02-25 Kai Jin , Pingzhong Tang , Shiteng Chen

In the same sense as classical logic is a formal theory of truth, the recently initiated approach called computability logic is a formal theory of computability. It understands (interactive) computational problems as games played by a…

Logic in Computer Science · Computer Science 2011-04-15 Giorgi Japaridze

Selection of input features such as relevant pieces of text has become a common technique of highlighting how complex neural predictors operate. The selection can be optimized post-hoc for trained models or incorporated directly into the…

Machine Learning · Computer Science 2019-10-29 Shiyu Chang , Yang Zhang , Mo Yu , Tommi S. Jaakkola

We extend the study of the iterated elimination of strictly dominated strategies (IESDS) from Nash strategic games to a class of qualitative games. Also in this case, the IESDS process leads us to a kind of 'rationalizable' result. We…

Computer Science and Game Theory · Computer Science 2013-03-29 Monica Patriche

This paper has a twofold scope. The first one is to clarify and put in evidence the isomorphic character of two theories developed in quite different fields: on one side, threshold logic, on the other side, simple games. One of the main…

Computer Science and Game Theory · Computer Science 2017-07-10 Josep Freixas , Marc Freixas , Sascha Kurz

Justification theory is a unifying semantic framework. While it has its roots in non-monotonic logics, it can be applied to various areas in computer science, especially in explainable reasoning; its most central concept is a justification:…

Artificial Intelligence · Computer Science 2020-09-23 Simon Marynissen , Bart Bogaerts , Marc Denecker

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

The paper proposes a fresh look at the concept of goal and advances that motivational attitudes like desire, goal and intention are just facets of the broader notion of (acceptable) outcome. We propose to encode the preferences of an agent…

Logic in Computer Science · Computer Science 2022-09-13 Guido Governatori , Francesco Olivieri , Simone Scannapieco , Antonino Rotolo , Matteo Cristani

This paper offers a new perspective to ease the challenge of domain generalization, which involves maintaining robust results even in unseen environments. Our design focuses on the decision-making process in the final classifier layer.…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Liang Chen , Yong Zhang , Yibing Song , Anton van den Hengel , Lingqiao Liu

In [Van Benthem 2007] the concept of a public announcement is used to study the effect of the iterated elimination of strictly dominated strategies. We offer a simple generalisation of this approach to cover arbitrary strategic games and…

Computer Science and Game Theory · Computer Science 2010-12-24 Krzysztof R. Apt , Jonathan A. Zvesper

Rationalization empowers deep learning models with self-explaining capabilities through a cooperative game, where a generator selects a semantically consistent subset of the input as a rationale, and a subsequent predictor makes predictions…

Artificial Intelligence · Computer Science 2023-12-18 Wei Liu , Haozhao Wang , Jun Wang , Zhiying Deng , YuanKai Zhang , Cheng Wang , Ruixuan Li

We provide a formal, simple and intuitive theory of rational decision making including sequential decisions that affect the environment. The theory has a geometric flavor, which makes the arguments easy to visualize and understand. Our…

Machine Learning · Computer Science 2012-02-10 Peter Sunehag , Marcus Hutter