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 2
The Competitive Ratio of Online Budgeted Allocation is Strictly Smaller than $1-1/e$
A well-known conjecture in online algorithms is that the (randomized) competitive ratio of online budgeted allocation is $1-1/e$.When Is a Game a Markov Decision Process? Correspondences Between Game Theory and Reinforcement Learning
Reinforcement learning and game theory describe the same object from two sides.Strategic Tanking in Stable Matching Markets
Motivated by a broad literature in psychology, organizational behavior, and matching markets, we introduce strategic tanking: an agent deliberately makes themselves less attractive to selected…Online Fair Division of Chores with Upgrade Recourse
We study the online fair division of indivisible chores among $n$ agents under upgrade recourse, where earlier assignments may be revised but each chore previously assigned to an agent must be…Persistence of Bounded Rationality in Financial Markets: An Evolutionary Game-Theoretic Model
Classical theory predicts that irrational traders lose money to rational traders and are eventually driven out of the market.How a group that cannot communicate knows itself by its enemy
Teams that cannot communicate seem stuck with what each member sees.Fair Recommender Systems for Intersecting Groups
Recommendation systems that optimize for the average user can fail to capture the preferences of diverse demographic groups.Renegotiable Options Fail to Prevent Hold-Up Between Two Profit-Maximizing Frontier LLM Agents
Do contract terms that protect investment between people also protect it between profit-maximizing language-model agents?What Can Firms Do in the Face of Model Distillation?
Model distillation has become a major concern in the rapidly growing generative AI discourse.Vendster: An Evaluation Arena to Investigate How Forecasting Tool Quality Affects LLM Agent Behaviors in Buyer-Vendor Negotiation
Time-series forecasters are ranked almost entirely by accuracy metrics, but a forecast's decision value, its effect on the downstream decision, need not track accuracy and is rarely measured.Game-Theoretic Foundations for Undiscounted Bisimulation Metrics
Bisimulation metrics offer a principled notion of task-relevant state similarity in reinforcement learning, but existing constructions and methods are largely confined to discounted MDPs, where…PDE-Based Bounds on Optimal Exponents in Active Simple Hypothesis Testing
We present general upper and lower bounds on the optimal error exponent for the Active Simple Hypothesis Testing (ASHT) problem.Impossibility of No-Regret in Multi-Agent Bidding
We consider $T$ repeated second-price auctions across $n$ pacing bidders with i.i.d. item arrivals, and show that it is computationally impossible for all bidders to achieve no-regret simultaneously…Conservative Policy Iteration For Zero-Sum POSGs
Occupancy-state reductions make dynamic programming possible for zero-sum partially observable stochastic games (zs-POSGs).Game-Theoretic Solvers with Bayesian Opponent Modeling and Moral Rhetoric Framing for GLEE
We describe the agent we submitted to the GLEE Competition, which plays bargaining, negotiation, and persuasion games against a shared pool of human and AI opponents.Strategyproof Deep Reinforcement Learning for Online Resource Allocation
Online resource allocation faces two coupled challenges: (1) allocating scarce resources efficiently under uncertain future demand, and (2) ensuring that agents report task valuations and…Multi-Agent Reinforcement Learning for Global Climate Policy Cooperation
International climate policy requires coordination among countries whose mitigation decisions impose local costs but generate global benefits.Order-selection Prophet Inequality (Almost) Goes I.I.D
We study the order-selection prophet inequality.Game theory of academic effort and hiring in the age of AI
Many academic disciplines (in particular, mathematics and the theoretical sciences) face difficult questions about how to adapt their practices to the rise of highly capable artificial intelligence…Seeing Through Distractions: Context-Stable Attribution via the Least Core
Shapley-value-based explanations are widely used for feature attribution in machine learning.