Tootfinder

Temporal Cooperative Games
Ashwin Goyal, Drashthi Doshi, Swaprava Nath
https://arxiv.org/abs/2510.11255 https://arxiv.org/pdf/2510.11255

Temporal Cooperative Games
Classical cooperative game theory assumes that the worth of a coalition depends only on the set of agents involved, but in practice, it may also depend on the order in which agents arrive. Motivated by such scenarios, we introduce temporal cooperative games (TCG), where the worth $v$ becomes a function of the sequence of agents $π$ rather than just the set $S$. This shift calls for rethinking the underlying axioms. A key property in this temporal framework is the incentive for optimal arrival …

Nonlocal Games Through Communication Complexity and Quantum Cryptography
Pierre Botteron
https://arxiv.org/abs/2510.09457 https://arxiv.org/pdf/2510.09457

Nonlocal Games Through Communication Complexity and Quantum Cryptography
This thesis explores foundational aspects of quantum information theory and quantum cryptography. First, we investigate quantum correlations in interactive settings, including the CHSH and graph isomorphism games. We aim to distinguish quantum correlations from non-signaling correlations by leveraging the principle of communication complexity. To this end, we employ techniques such as distributed computation, majority-function-based distillation protocols, the algebraic and geometric properti…

Fast and the Furious: Hot Starts in Pursuit-Evasion Games
Gabriel Smithline, Scott Nivison
https://arxiv.org/abs/2510.10830 https://arxiv.org/pdf/2510.1083…

Fast and the Furious: Hot Starts in Pursuit-Evasion Games
Effectively positioning pursuers in pursuit-evasion games without prior knowledge of evader locations remains a significant challenge. A novel approach that combines game-theoretic control theory with Graph Neural Networks is introduced in this work. By conceptualizing pursuer configurations as strategic arrangements and representing them as graphs, a Graph Characteristic Space is constructed via multi-objective optimization to identify Pareto-optimal configurations. A Graph Convolutional Netwo…

Conversational Implicatures: Modelling Relevance Theory Probabilistically
Christoph Unger, Hendrik Buschmeier
https://arxiv.org/abs/2509.22354 https://arxi…

Conversational Implicatures: Modelling Relevance Theory Probabilistically
Recent advances in Bayesian probability theory and its application to cognitive science in combination with the development of a new generation of computational tools and methods for probabilistic computation have led to a 'probabilistic turn' in pragmatics and semantics. In particular, the framework of Rational Speech Act theory has been developed to model broadly Gricean accounts of pragmatic phenomena in Bayesian terms, starting with fairly simple reference games and covering ever more compl…

Evolution of social behaviors in noisy environments
Guocheng Wang, Qi Su, Long Wang, Joshua B. Plotkin
https://arxiv.org/abs/2510.05521 https://arxiv.org/p…

Evolution of social behaviors in noisy environments
Evolutionary game theory offers a general framework to study how behaviors evolve by social learning in a population. This body of theory can accommodate a range of social dilemmas, or games, as well as real-world complexities such as spatial structure or behaviors conditioned on reputations. Nonetheless, this approach typically assumes a deterministic payoff structure for social interactions. Here, we extend evolutionary game theory to account for random changes in the social environment, so t…

Well it's pretty unpolished, but it works. Made good progress on my web manager / installer for games.
Currently supports Debian and Ubuntu, (though technically works on any Linux distro in theory), and supports:
https://github.c…

The Theory of Strategic Evolution: Games with Endogenous Players and Strategic Replicators
Kevin Vallier
https://arxiv.org/abs/2512.07901 https://arxiv.org/pdf/2512.07901 https://arxiv.org/html/2512.07901
arXiv:2512.07901v1 Announce Type: new
Abstract: This paper develops the Theory of Strategic Evolution, a general model for systems in which the population of players, strategies, and institutional rules evolve together. The theory extends replicator dynamics to settings with endogenous players, multi level selection, innovation, constitutional change, and meta governance. The central mathematical object is a Poiesis stack: a hierarchy of strategic layers linked by cross level gain matrices. Under small gain conditions, the system admits a global Lyapunov function and satisfies selection, tracking, and stochastic stability results at every finite depth. We prove that the class is closed under block extension, innovation events, heterogeneous utilities, continuous strategy spaces, and constitutional evolution. The closure theorem shows that no new dynamics arise at higher levels and that unrestricted self modification cannot preserve Lyapunov structure. The theory unifies results from evolutionary game theory, institutional design, innovation dynamics, and constitutional political economy, providing a general mathematical model of long run strategic adaptation.
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Crosslisted article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- GRPO-GCC: Enhancing Cooperation in Spatial Public Goods Games via Group Relative Policy Optimizat...
Zhaoqilin Yang, Chanchan Li, Tianqi Liu, Hongxin Zhao, Youliang Tian

Proceedings of the Sixteenth International Symposium on Games, Automata, Logics, and Formal Verification
Giorgio Bacci (Aalborg University, Denmark), Adrian Francalanza (University of Malta)
https://arxiv.org/abs/2509.13258

Proceedings of the Sixteenth International Symposium on Games, Automata, Logics, and Formal Verification
This volume contains the proceedings of GandALF 2025, the Sixteenth International Symposium on Games, Automata, Logics, and Formal Verification. GandALF 2025 took place on 16-17th September 2025, in Valletta, Malta. The aim of GandALF 2025 is to bring together researchers from academia and industry who are actively working in the fields of Games, Automata, Logics, and Formal Verification. The idea is to cover an ample spectrum of themes, ranging from theory to applications, and stimulate cross-…

Various Diamond Properties in Combinatorial Game Theory
Keiichirou Kusakari, Tomoaki Abuku
https://arxiv.org/abs/2509.21744 https://arxiv.org/pdf/2509.2174…

Various Diamond Properties in Combinatorial Game Theory
We investigate conditions under which positions in combinatorial games admit simple values. We introduce a unified diamond framework, the $\Diamond_A$-property ($A\in\{\mathbb{Z},\mathbb{D}$), for sets of positions closed under options. Under certain conditions, this framework guarantees that all values are integers, dyadic rationals, or pairs $\{m|n\}$ (on $\mathbb{Z}$ or $\mathbb{D}$). As an application, we establish that every position in \textsc{Yashima} game on bipartite graphs has an…

A non-sequential arithmetical theory with pairing
Juvenal Murwanashyaka
https://arxiv.org/abs/2509.15191 https://arxiv.org/pdf/2509.15191

A non-sequential arithmetical theory with pairing
Albert Visser has shown that Robinson's $ \mathsf{Q} $ and Gregorczyk's $ \mathsf{TC} $ are not sequential by showing that these theories are not even poly-pair theories, which, in a strong sense, means these theories lack pairing. In this paper, we use Ehrenfeucht-Fraïssé games to show that the theory $ \mathsf{Q} + Θ$ we obtain by extending Robinson's $ \mathsf{Q} $ with an axiom $ Θ$ which says that the map $ π(x, y ) = (x+y)^2 + x $ is a pairing function is not sequential; in fact, we …

Extending Games beyond the Finite Horizon
Kiri Sakahara, Takashi Sato
https://arxiv.org/abs/2510.08453 https://arxiv.org/pdf/2510.08453

Extending Games beyond the Finite Horizon
This paper argues that the finite horizon paradox, where game theory contradicts intuition, stems from the limitations of standard number systems in modelling the cognitive perception of infinity. To address this issue, we propose a new framework based on Alternative Set Theory (AST). This framework represents different cognitive perspectives on a long history of events using distinct topologies. These topologies define an indiscernibility equivalence that formally treats huge, indistinguishabl…

Scale-Invariant Regret Matching and Online Learning with Optimal Convergence: Bridging Theory and Practice in Zero-Sum Games
Brian Hu Zhang, Ioannis Anagnostides, Tuomas Sandholm
https://arxiv.org/abs/2510.04407

Scale-Invariant Regret Matching and Online Learning with Optimal Convergence: Bridging Theory and Practice in Zero-Sum Games
A considerable chasm has been looming for decades between theory and practice in zero-sum game solving through first-order methods. Although a convergence rate of $T^{-1}$ has long been established since Nemirovski's mirror-prox algorithm and Nesterov's excessive gap technique in the early 2000s, the most effective paradigm in practice is *counterfactual regret minimization*, which is based on *regret matching* and its modern variants. In particular, the state of the art across most benchmarks …

On Dynamic Programming Theory for Leader-Follower Stochastic Games
Jilles Steeve Dibangoye, Thibaut Le Marre, Ocan Sankur, Fran\c{c}ois Schwarzentruber
https://arxiv.org/abs/2512.05667 https://arxiv.org/pdf/2512.05667 https://arxiv.org/html/2512.05667
arXiv:2512.05667v1 Announce Type: new
Abstract: Leader-follower general-sum stochastic games (LF-GSSGs) model sequential decision-making under asymmetric commitment, where a leader commits to a policy and a follower best responds, yielding a strong Stackelberg equilibrium (SSE) with leader-favourable tie-breaking. This paper introduces a dynamic programming (DP) framework that applies Bellman recursion over credible sets-state abstractions formally representing all rational follower best responses under partial leader commitments-to compute SSEs. We first prove that any LF-GSSG admits a lossless reduction to a Markov decision process (MDP) over credible sets. We further establish that synthesising an optimal memoryless deterministic leader policy is NP-hard, motivating the development of {\epsilon}-optimal DP algorithms with provable guarantees on leader exploitability. Experiments on standard mixed-motive benchmarks-including security games, resource allocation, and adversarial planning-demonstrate empirical gains in leader value and runtime scalability over state-of-the-art methods.
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Replaced article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- Solving Football by Exploiting Equilibrium Structure of 2p0s Differential Games with One-Sided In...
Mukesh Ghimire, Lei Zhang, Zhe Xu, Yi Ren

Replaced article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- Cumulative Games: Who is the current player?
Urban Larsson, Reshef Meir, Yair Zick
https://arxiv.org/abs/2005.06326
- Contest Design with Threshold Objectives
Edith Elkind, Abheek Ghosh, Paul W. Goldberg
https://arxiv.org/abs/2109.03179
- Deep Learning Meets Mechanism Design: Key Results and Some Novel Applications
V. Udaya Sankar, Vishisht Srihari Rao, Y. Narahari
https://arxiv.org/abs/2401.05683 https://mastoxiv.page/@arXiv_csGT_bot/111741115483021453
- Charting the Shapes of Stories with Game Theory
Daskalakis, Gemp, Jiang, Leme, Papadimitriou, Piliouras
https://arxiv.org/abs/2412.05747 https://mastoxiv.page/@arXiv_csGT_bot/113627246220336424
- Computing Evolutionarily Stable Strategies in Multiplayer Games
Sam Ganzfried
https://arxiv.org/abs/2511.20859 https://mastoxiv.page/@arXiv_csGT_bot/115620508246637361
- Autodeleveraging: Impossibilities and Optimization
Tarun Chitra
https://arxiv.org/abs/2512.01112 https://mastoxiv.page/@arXiv_csGT_bot/115649040881525135
- Static Pricing Guarantees for Queueing Systems
Jacob Bergquist, Adam N. Elmachtoub
https://arxiv.org/abs/2305.09168 https://mastoxiv.page/@arXiv_csDS_bot/110382625621173269
- Game of arrivals at a two queue network with heterogeneous customer routes
Agniv Bandyopadhyay, Sandeep Juneja
https://arxiv.org/abs/2310.18149 https://mastoxiv.page/@arXiv_csPF_bot/111322112226936579
- Characterization of Priority-Neutral Matching Lattices
Clayton Thomas
https://arxiv.org/abs/2404.02142 https://mastoxiv.page/@arXiv_econTH_bot/112205968984928881
- Seven kinds of equivalent models for generalized coalition logics
Zixuan Chen, Fengkui Ju
https://arxiv.org/abs/2501.05466 https://mastoxiv.page/@arXiv_csLO_bot/113819715349259373
- Matching Markets Meet LLMs: Algorithmic Reasoning with Ranked Preferences
Hadi Hosseini, Samarth Khanna, Ronak Singh
https://arxiv.org/abs/2506.04478 https://mastoxiv.page/@arXiv_csAI_bot/114635186215388479
toXiv_bot_toot

Replaced article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- Optimal Modified Feedback Strategies in LQ Games under Control Imperfections
Mahdis Rabbani, Navid Mojahed, Shima Nazari

Grouped Satisficing Paths in Pure Strategy Games: a Topological Perspective
Yanqing Fu, Chao Huang, Chenrun Wang, Zhuping Wang
https://arxiv.org/abs/2509.23157 https://

Grouped Satisficing Paths in Pure Strategy Games: a Topological Perspective
In game theory and multi-agent reinforcement learning (MARL), each agent selects a strategy, interacts with the environment and other agents, and subsequently updates its strategy based on the received payoff. This process generates a sequence of joint strategies $(s^t)_{t \geq 0}$, where $s^t$ represents the strategy profile of all agents at time step $t$. A widely adopted principle in MARL algorithms is "win-stay, lose-shift", which dictates that an agent retains its current strategy if it ac…

Crosslisted article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- AI-Generated Compromises for Coalition Formation: Modeling, Simulation, and a Textual Case Study
Eyal Briman, Ehud Shapiro, Nimrod Talmon
https://arxiv.org/abs/2512.05983 https://mastoxiv.page/@arXiv_csMA_bot/115688474865840195
- Going All-In on LLM Accuracy: Fake Prediction Markets, Real Confidence Signals
Michael Todasco
https://arxiv.org/abs/2512.05998
- Small-Gain Nash: Certified Contraction to Nash Equilibria in Differentiable Games
Vedansh Sharma
https://arxiv.org/abs/2512.06791 https://mastoxiv.page/@arXiv_csLG_bot/115689591150148735
- Characterizing Lane-Changing Behavior in Mixed Traffic
Sungyong Chung, Alireza Talebpour, Samer H. Hamdar
https://arxiv.org/abs/2512.07219 https://mastoxiv.page/@arXiv_csMA_bot/115688571373683355
- Understanding LLM Agent Behaviours via Game Theory: Strategy Recognition, Biases and Multi-Agent ...
Kiet Huynh, et al.
https://arxiv.org/abs/2512.07462 https://mastoxiv.page/@arXiv_csMA_bot/115688610063828863
- Optimal Auction Design under Costly Learning
Kemal Ozbek
https://arxiv.org/abs/2512.07798 https://mastoxiv.page/@arXiv_econTH_bot/115688939067758036
toXiv_bot_toot

Cooperation in Bilateral Generalized Network Creation
Hans Gawendowicz, Pascal Lenzner, Lukas Weyand
https://arxiv.org/abs/2510.00239 https://arxiv.org/pdf…

Cooperation in Bilateral Generalized Network Creation
Studying the impact of cooperation in strategic settings is one of the cornerstones of algorithmic game theory. Intuitively, allowing more cooperation yields equilibria that are more beneficial for the society of agents. However, for many games it is still an open question how much cooperation is actually needed to ensure socially good equilibria. We contribute to this research endeavor by analyzing the benefits of cooperation in a network formation game that models the creation of communicatio…

Replaced article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- Algorithms and Complexity for Computing Nash Equilibria in Adversarial Team Games
Anagnostides, Kalogiannis, Panageas, Vlatakis-Gkaragkounis, McAleer

Crosslisted article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- Learning in Stackelberg Markov Games
Jun He, Andrew L. Liu, Yihsu Chen
https://

Replaced article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- A Stable-Set Bound and Maximal Numbers of Nash Equilibria in Bimatrix Games
Constantin Ickstadt, Thorsten Theobald, Bernhard von Stengel

Crosslisted article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- Private Markovian Equilibrium in Stackelberg Markov Games for Smart Grid Demand Response
Siying Huang, Yifen Mu, Ge Chen