Theory & Algorithms · Computer Science & AI
Computer Science & Game Theory
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252 papers, from 4 September 2026 to 5 November 2026: 252 arXiv preprints.
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Newest papers, page 11
Building Socio-Affective Artificial Intelligence for Interactive Multi-Agent Simulations
The objective of this article is to provide design principles and a software architecture for enabling interaction between humans and multiple agents in simulated dynamic worlds.An Incremental Algorithm for Checking the Possibility of Braess Paradox in Dynamic Nets
Braess paradox is a well-known phenomenon that originates when latency at Wardrop equilibrium in traffic networks decreases because of removing edges.The Facility Advantage in the One-Round Discrete Voronoi Game on a Line
In the one-round discrete Voronoi game a multiset $V$ of $n$ voters on a line is given; player P places $k$ facilities, player Q then places $\ell$, and each voter is won by the nearer facility…Optimal High-Order Methods for Solving Monotone Variational Inequalities
We study second- and higher-order methods for solving smooth monotone variational inequalities (MVI).Algorithmic Collusion and the Complexity of Information-Value-Free Equilibria
A (coarse) correlated equilibrium (CE) is information-value-free (IVF) if a player can match the payoff obtained from recommendations by committing to a fixed action.A Horizon-Independent Regret Bound for Optimistic Hedge in General-Sum Games
Can simple learning rules keep their regret bounded in self-play?Cross-Platform vs Native Mobile Development: An Empirical Study of Software Quality Trade-offs
Cross-platform mobile frameworks promise code reuse, shorter delivery cycles, and lower implementation effort, but their trade-offs relative to native development remain difficult to assess…Fair Prophets
We initiate the study of $α$-fair prophet inequalities.Guiding Agents of Quantum Games to Equilibrium using Matrix Exponential Fixed-Point Iteration
In recent years, quantum game theory has gained significant attention as a framework for studying decision-making in multi-agent systems using quantum principles.Multiplicative Optimism for Constant Regret in Games
We introduce Multiplicatively Optimistic Regret Matching (MORM), an uncoupled learning rule for finite general-sum games.Strategic Classification Has a Missing Lever: Audit Risk
Strategic classification studies how a decision maker should choose a classifier when the agents being classified can adjust their features in response to it.Steering Equilibrium Selection in Regularized Self-Play via the Reference Policy
Regularized self-play -- the family behind DeepNash's Stratego play -- drives a two-player zero-sum policy to a Nash equilibrium by best-responding to a slowly moving, entropy-regularized reference…Learning Principal-Agent Contracts for Equitable Smallholder Carbon Farming under Moral Hazard and Adverse Selection
Agricultural soils are a major untapped carbon sink.ABM-SIRTEM: A Hybrid Agent-Based and Epidemiological Model for Pandemic Response
The COVID-19 pandemic has had profound impacts on global health, social structures, and economies.Equilibria of Round-Robin: Computational Hardness and Fairness for Few Subadditive Agents
The round-robin procedure is a simple and well-studied fair division mechanism where agents pick goods in turns.Efficient Nash Equilibrium Computation for Cybersecurity Games
Game-theoretic analyses of cyber defence often compute equilibria of games whose payoffs exist only as the output of a simulator.Anchored Sequential Deliberation
Sequential deliberation is a mechanism for collective decision making: at each round, a uniformly randomly selected pair is asked to revise a collective outcome, which then becomes the reference…Constant Swap Regret in General-Sum Games via Two-Scale Higher-Order Optimism
We give deterministic and uncoupled learning dynamics for finite multiplayer general-sum games under full-information feedback that achieve constant individual swap regret in self-play, independent…Intervention problems in the Linear Threshold Model: A general formulation and new results
We study an optimal intervention problem for linear threshold models.Online Allocation using Few Samples
We study online allocation problems where $n$ requests over $m$ resources arrive in an adversarial order and must be served immediately and irrevocably.