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
Learning and Steering in Incomplete-Information Games
In many modern multi-agent systems, a mediator seeks to influence strategic decision dynamics using only outcome-level feedback and without knowing agents' utilities.Regret Bounds for Profit Maximization in Bilateral Trade: Learning the Best Posted-Price Mechanism
Bilateral trade models the task of intermediating between two strategic agents, a seller and a buyer, willing to trade a good for which they hold private valuations.Sublinear Metric Distortion for Matching
We study metric distortion in one-sided matching.AI-Assisted Classification under Correlation Neglect and Trust
When does an AI assistant improve human decision-making, and when does it hurt?Offline Learning of Reserve Prices from Censored Bids
We study how a seller can learn a reserve price for a second-price auction from censored historical bid data.Regret Bounds for Market Making with Persistent Orders
We study adversarial market making with orders that remain active until execution.Prophet Secretary for Matroids and XOS Valuations: A Strict Separation at $1-1/e$
The matroid prophet-secretary problem asks an online algorithm to select an independent set of elements whose nonnegative values are drawn independently and revealed in uniformly random order.Online Edge-Weighted Matching Beyond 0.55
We give a $0.556195$-competitive randomized algorithm for edge-weighted online bipartite matching with free disposal, improving the $0.5368$ guarantee of Blanc and Charikar.Optimistic Hedge in General-Sum Games: Fundamental Limits and Regret Bounds via Temporal Approximation
Optimistic Hedge, a multiplicative weight update with one step of extrapolation, is one of the most natural regret-minimizing dynamics for games, and characterizing its regret has been a…Polynomial-Time Computation of Extensive-Form Proper Equilibria in Two-Player Zero-Sum Games
We give a deterministic polynomial-time algorithm for computing an exact extensive-form proper equilibrium in a finite two-player zero-sum extensive-form game with perfect recall and rational data.Best-of-Many-Worlds MMS Allocation for Chores with Sublinear Disposals
We study randomized allocations (lotteries) of indivisible chores under additive costs and introduce the notion of MMS1, which requires each agent's bundle to satisfy the maximin share (MMS) bound…Linear Equivalence of Full Weight Spectrum Cyclic Orbit Codes
We determine the linear-equivalence classes within the two families of full weight spectrum one-orbit cyclic subspace codes.Efficient Equilibrium Computation in Colonel Blotto Games
Colonel Blotto is a fundamental resource-allocation game in which two players divide their budgets across battlefields, and the higher allocation on each battlefield wins its value.Logarithmic Regret for Alternating Mirror Descent
Alternating online mirror descent (AltOMD) is a simple learning rule for zero-sum games, which improves upon simultaneous OMD numerically and theoretically.Learning vs. Optimizing Players in Budgeted Games
We study repeated general games over $T$ rounds between a utility-maximizing optimizer and a learning agent, where budget constraints couple the players' decisions across rounds.Neural networks and games
Hopfield neural networks and noncooperative games provide seemingly different approaches to understanding how collective outcomes emerge from local interactions.On the Convergence of Alternating Regret Matching Algorithms
Alternating updates, that is, where each player is updated in turn, tend to typically perform better in regret matching algorithms than simultaneous updates.Classification Aggregation with Multiple Memberships
People face the problem of classifying objects into categories while aggregating their opinions.A Compute Center Anyone Can Join: A Peer-to-Peer System for AI Inference
Today, most people obtain AI inference by buying it from a small number of organizations that run large data centers, while many GPUs owned by individuals and small institutions sit idle for much of…How Much Can Approximate Equilibria Change the Social Cost of Selfish Routing?
We study approximate Nash equilibria in nonatomic congestion games, with the goal of understanding how much the social cost can change when the equilibrium condition is relaxed.