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Related papers: From open learners to open games

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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

A supervised learning algorithm searches over a set of functions $A \to B$ parametrised by a space $P$ to find the best approximation to some ideal function $f\colon A \to B$. It does this by taking examples $(a,f(a)) \in A\times B$, and…

Category Theory · Mathematics 2019-05-02 Brendan Fong , David I. Spivak , Rémy Tuyéras

We show open games cover extensive form games with both perfect and imperfect information. Doing so forces us to address two current weaknesses in open games: the lack of a notion of player and their agency within open games, and the lack…

Computer Science and Game Theory · Computer Science 2022-11-04 Matteo Capucci , Neil Ghani , Jérémy Ledent , Fredrik Nordvall Forsberg

Compositional Game Theory is a new, recently introduced model of economic games based upon the computer science idea of compositionality. In it, complex and irregular games can be built up from smaller and simpler games, and the equilibria…

Computer Science and Game Theory · Computer Science 2017-11-22 Neil Ghani , Clemens Kupke , Alasdair Lambert , Fredrik Nordvall Forsberg

We begin by reviewing and proving the basic facts of combinatorial game theory. We then consider scoring games (also known as Milnor games or positional games), focusing on the "fixed-length" games for which all sequences of play terminate…

Combinatorics · Mathematics 2011-07-27 Will Johnson

Although recent work in AI has made great progress in solving large, zero-sum, extensive-form games, the underlying assumption in most past work is that the parameters of the game itself are known to the agents. This paper deals with the…

Machine Learning · Computer Science 2018-06-29 Chun Kai Ling , Fei Fang , J. Zico Kolter

Many emerging applications - such as adversarial training, AI alignment, and robust optimization - can be framed as zero-sum games between neural nets, with von Neumann-Nash equilibria (NE) capturing the desirable system behavior. While…

Machine Learning · Computer Science 2025-12-02 Deep Patel , Emmanouil-Vasileios Vlatakis-Gkaragkounis

Spoiler-Duplicator games are used in finite model theory to examine the expressive power of logics. Their strategies have recently been reformulated as coKleisli maps of game comonads over relational structures, providing new results in…

Logic in Computer Science · Computer Science 2025-06-17 Yoàv Montacute , Glynn Winskel

This paper provides a unified view to explain different adversarial attacks and defense methods, \emph{i.e.} the view of multi-order interactions between input variables of DNNs. Based on the multi-order interaction, we discover that…

Machine Learning · Computer Science 2021-11-09 Jie Ren , Die Zhang , Yisen Wang , Lu Chen , Zhanpeng Zhou , Yiting Chen , Xu Cheng , Xin Wang , Meng Zhou , Jie Shi , Quanshi Zhang

In this paper we analyse two-player games by their response graphs. The response graph has nodes which are strategy profiles, with an arc between profiles if they differ in the strategy of a single player, with the direction of the arc…

Computer Science and Game Theory · Computer Science 2023-02-15 Oliver Biggar , Iman Shames

When mathematical modelling is applied to capture a complex system, multiple models are often created that characterize different aspects of that system. Often, a model at one level will produce a prediction which is contradictory at…

Computers and Society · Computer Science 2022-05-19 Abeba Birhane , David J. T. Sumpter

Classify simple games into sixteen "types" in terms of the four conventional axioms: monotonicity, properness, strongness, and nonweakness. Further classify them into sixty-four classes in terms of finiteness (existence of a finite carrier)…

Computer Science and Game Theory · Computer Science 2011-07-05 Masahiro Kumabe , H. Reiju Mihara

We train two neural networks adversarially to play static games. At each iteration, a row and column network observe a new random bimatrix game and output individual mixed strategies. The parameters of each network are independently updated…

Theoretical Economics · Economics 2025-05-09 Daniele Condorelli , Massimiliano Furlan

Pursuing a new approach to the study of infinite games in combinatorics, we introduce the categories $\mathbf{Game}_{A}$ and $\mathbf{Game}_{B}$ and improve some classical results concerning topological games related to the duality between…

General Topology · Mathematics 2025-11-11 Matheus Duzi , Paul Szeptycki , Walter Tholen

In "Backprop as functor", the authors show that the fundamental elements of deep learning -- gradient descent and backpropagation -- can be conceptualized as a strong monoidal functor Para(Euc)$\to$Learn from the category of parameterized…

Category Theory · Mathematics 2025-06-09 David I. Spivak

We introduce a formal notion of defendability against backdoors using a game between an attacker and a defender. In this game, the attacker modifies a function to behave differently on a particular input known as the "trigger", while…

Machine Learning · Computer Science 2025-02-12 Paul Christiano , Jacob Hilton , Victor Lecomte , Mark Xu

Fixpoints are ubiquitous in computer science as they play a central role in providing a meaning to recursive and cyclic definitions. Bisimilarity, behavioural metrics, termination probabilities for Markov chains and stochastic games are…

Logic in Computer Science · Computer Science 2025-07-23 Paolo Baldan , Richard Eggert , Barbara König , Timo Matt , Tommaso Padoan

Evolutionary game theory studies populations that change in response to an underlying game. Often, the functional form relating outcome to player attributes or strategy is complex, preventing mathematical progress. In this work, we…

Computer Science and Game Theory · Computer Science 2025-11-25 Pablo Lechon-Alonso , Andrew Dennehy , Ruizheng Bai , Nicolas Sanchez , Derek K. Wise , David Sewell , David Rosenbluth , Alexander Strang

Differential games with asymmetric information were introduced by Cardaliaguet (2007). As in repeated games with lack of information on both sides (Aumann and Maschler (1995)), each player receives a private signal (his type) before the…

Optimization and Control · Mathematics 2014-03-31 Miquel Oliu-Barton

As an alternative view to the graph formation models in the statistical physics community, we introduce graph formation models using \textit{network formation} through selfish competition as an approach to modeling graphs with particular…

Optimization and Control · Mathematics 2015-03-13 Shaun Lichter , Christopher Griffin , Terry Friesz
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