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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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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
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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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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
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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…

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 …

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