Theory & Algorithms · Computer Science & AI
Computer Science & Game Theory
The newest papers in Computer Science & Game Theory that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
252 papers, from 4 September 2026 to 5 November 2026: 252 arXiv preprints.
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Newest papers, page 13
Deriving the Pure Price of Anarchy for Networked Resource Allocation Games
This work considers multi-agent coordination with arbitrary information networks among the agents using a game-theoretic approach.Rank Without an Oracle: Deviation-Aware Interaction-Rank Selection from Offline Multi-Agent Logs
Offline multi-agent payoff models are estimated under a logging distribution but used on distributions induced by learned solutions and unilateral deviations.Entropic Risk-Sensitive Evolutionary Learning and Equilibrium Selection in Coordination Games
We study risk-sensitive evolutionary learning dynamics and their long-run equilibrium selection behaviors in coordination games.Exact-Form Regret for Gradient Descent, Mirror Descent and Follow-the-Regularized-Leader
Online gradient descent is usually studied through external regret, where the learner competes with fixed alternatives.Input-to-State Stability Framework for Fully Distributed Primal-Dual Dynamics for Quadratic GNEPs Without Multiplier Consensus
Generalized Nash Equilibrium Problems (GNEPs) often arise in multi-agent engineering applications that require distributed algorithms.Protocol effects on feature-based hardware-Trojan detection across Trust-Hub families
Trust-Hub reuses host circuits: several files differ mainly in the inserted Trojan.Riemannian Optimization for Multi-Player Quantum Games on Product Unitary Manifolds
Quantum game theory is an extension of classical game theory that uses quantum principles in game theory.The Internal Anatomy of Strategic Choice in Large Language Models
Large language models act as strategic agents and models of human choice, yet choosing like a strategic agent does not mean computing like one.Guiding Worker Self-Selection in Crowdsourcing Contests: An LLM-Augmented Algorithmic Approach
Crowdsourcing platforms coordinate large pools of online workers who strategically choose which contests to enter and how much effort to invest.Sequential Offering in On-Demand Platforms: On the Optimality of Greedy Ranking
On-demand platforms face the fundamental challenge of fulfilling time-sensitive jobs with independent workers who may decline offers.Strategic Facility Location in Euclidean Spaces
The strategic facility location problem is defined as follows: $n$ agents report their location in a metric space, and the objective is to design a \emph{mechanism} deciding the (possibly…Optimal Rates for Agentic Networked Information Aggregation
Building on the pioneering paper of Kearns, Roth, and Ryu (SODA'26), we study information aggregation in a networked learning model.