60 papers
This paper introduces a meta-game framework to evaluate the emergence of algorithmic collusion under test-time constraints by modeling agents with pretrained policies and adaptation rules, revealing how rational choices and co-adaptation influence cooperative or competitive outcomes in repeated pricing games across various algorithmic strategies.
This paper demonstrates through game-theoretic analysis and simulation that the non-cooperative behavior of nodes under the 802.11 DCF and 802.11e MAC protocols leads to inefficient Nash equilibria, whereas decoupling channel allocation from individual transmission strategies can achieve superior throughput for all competing nodes.
This paper initiates the study of proportionality degree in participatory budgeting by establishing tight theoretical bounds for the Method of Equal Shares and Phragmen's Sequential Rule, demonstrating that despite their differing axiomatic properties, they achieve comparable quantitative proportionality, a finding further validated through extensive experiments on real-world datasets.
This paper proposes a game-theoretic framework for modeling stealthy Advanced Persistent Threat (APT) defense on attack graphs, where a defender strategically deploys sensors to secure critical assets against an MDP-based attacker operating under asymmetric temporal dynamics and varying levels of informational knowledge.
This paper introduces a two-stage stochastic capacity expansion model for many-to-one matching markets that accounts for both exogenous preference uncertainty and endogenous strategic misreporting, proposing sample average approximation-based heuristics to optimize school capacities and improve student outcomes compared to deterministic approaches.
This paper introduces Platooning as a Service (PlaaS), a Stackelberg game-based decision-support framework that optimizes pricing and travel distance between service providers and users to enhance sustainable transportation, while analyzing how factors like government subsidies and vehicle velocity impact profitability and carbon emissions.
This paper introduces \texttt{electoral\_sim}, an open-source Python framework that simulates and compares various electoral systems across diverse voter preference distributions using Euclidean distance to the geometric median as a primary performance metric, including a novel theoretical benchmark based on a Boltzmann softmax kernel.
This paper characterizes margin-based voting rules by proving they are equivalent to rules satisfying the "Preferential Equality" axiom, which ensures that voters' identical pairwise preferences are treated with equal normative weight regardless of the voter's identity.
This paper proposes \texttt{RQRE-OVI}, an optimistic value iteration algorithm that computes the unique and smooth Risk-Sensitive Quantal Response Equilibrium (RQRE) in general-sum Markov games with linear function approximation, offering a principled trade-off between performance and robustness that outperforms traditional Nash equilibrium approaches in both theoretical guarantees and empirical stability.
This paper proposes CORA, a cooperative game-theoretic credit assignment method that utilizes core allocation and coalition sampling to effectively distribute global advantages among agents in multi-agent reinforcement learning, thereby overcoming the limitations of uniform sharing and enhancing coordinated optimal behavior.
This paper addresses the sensitivity of semivalue-based data valuation to utility selection by introducing a "spatial signature" framework that embeds data points into a lower-dimensional space, enabling a practical methodology to quantify and ensure the robustness of valuation results against utility variations.
This paper demonstrates that competing algorithmic agents using multi-armed bandit learning can spontaneously develop "naive collusion" through action synchronicity, even without knowledge of competitors, with the likelihood of such outcomes depending critically on whether the agents employ deterministic, greedy-in-the-limit, or persistently random policies.
This paper proposes a novel statistical learning framework for multi-item auctions that utilizes nonparametric density estimation and credible intervals to implement two cost-reducing strategies, which maintain key economic properties like incentive compatibility and fairness while outperforming alternative methods in both revenue maximization and implementation efficiency.
This study demonstrates through numerical simulations of a spatial trust game that inter-role rewards do not linearly promote trust, as excessive rewards can trigger non-return strategies that suppress cooperation, while moderately costly rewards are most effective at consolidating trust clusters.
This paper presents the biased interaction game as a versatile modeling tool for social systems, demonstrating how boundedly rational interactions under scarcity and bias naturally generate emergent hierarchies, inequality, and non-linear stability patterns while offering a framework to evaluate competing wealth redistribution philosophies like social welfare and universal basic income.
This paper demonstrates that large language models exhibit robust decision biases in two-arm bandit tasks, characterized by stubborn exploitation and low learning rates that persist across decoding parameters, thereby posing significant challenges for optimal human-AI collaboration.
This paper extends opinion dynamics to multiplex networks by modeling them as synchronous coordination games with merged and switching coupling mechanisms, using spectral analysis to demonstrate how cross-layer interactions can uniquely induce, accelerate, or disrupt global consensus compared to single-layer systems.
This paper introduces a new deterministic symmetric recursive algorithm designed to solve mean-payoff games.
This paper investigates concurrent graph games with distributed randomization where team players lack a shared random source, establishing that memoryless strategies suffice for the threshold problem (placing it in and proving NP-hardness) and that almost-sure reachability is NP-complete, while introducing the IRATL logic and a corresponding solver.
This paper develops a game-theoretic framework to analyze the incentives and efficiency losses in informal, privatized transit systems, demonstrating that targeted interventions like centralized routing and cross-subsidization can effectively mitigate performance gaps between decentralized profit-driven operations and optimal system outcomes.