Tootfinder

Complexity of the Existence of Constrained Secure Equilibria in Multi-Player Games
Hiroki Mizuno, Yoshiaki Takata, Hiroyuki Seki
https://arxiv.org/abs/2509.01870 https://…

Complexity of the Existence of Constrained Secure Equilibria in Multi-Player Games
We consider a multi-player non-zero-sum turn-based game (abbreviated as multi-player game) on a finite directed graph. A secure equilibrium (SE) is a strategy profile in which no player has the incentive to deviate from the strategy because no player can increase her own payoff or lower the payoff of another player. SE is a promising refinement of Nash equilibrium in which a player does not care the payoff of another player. In this paper, we discuss the decidability and complexity of the probl…

Solving Zero-Sum Games with Fewer Matrix-Vector Products
Ishani Karmarkar, Liam O'Carroll, Aaron Sidford
https://arxiv.org/abs/2509.04426 https://arxiv…

Solving Zero-Sum Games with Fewer Matrix-Vector Products
In this paper we consider the problem of computing an $ε$-approximate Nash Equilibrium of a zero-sum game in a payoff matrix $A \in \mathbb{R}^{m \times n}$ with $O(1)$-bounded entries given access to a matrix-vector product oracle for $A$ and its transpose $A^\top$. We provide a deterministic algorithm that solves the problem using $\tilde{O}(ε^{-8/9})$-oracle queries, where $\tilde{O}(\cdot)$ hides factors polylogarithmic in $m$, $n$, and $ε^{-1}$. Our result improves upon the state-of-the…

Paramount faces a backlash for settling with Trump; Democrat FCC Commissioner Anna Gomez says it "marks a dangerous precedent for the First Amendment" (Meg James/Los Angeles Times)
https://www.latimes.com/entertain…

Paramount faces backlash over its $16-million Trump settlement
Journalists and others said the payoff will embolden attacks by Trump and his allies on news outlets. Some called the settlement a stain on the proud legacy of CBS News.

Dilution, Diffusion and Symbiosis in Spatial Prisoner's Dilemma with Reinforcement Learning
Gustavo C. Mangold, Heitor C. M. Fernandes, Mendeli H. Vainstein
https://arxiv.org/abs/2507.02211

Dilution, Diffusion and Symbiosis in Spatial Prisoner's Dilemma with Reinforcement Learning
Recent studies in the spatial prisoner's dilemma games with reinforcement learning have shown that static agents can learn to cooperate through a diverse sort of mechanisms, including noise injection, different types of learning algorithms and neighbours' payoff knowledge.In this work, using an independent multi-agent Q-learning algorithm, we study the effects of dilution and mobility in the spatial version of the prisoner's dilemma. Within this setting, different possible actions for the algor…

On Zero-sum Game Representation for Replicator Dynamics
Haoyu Yin, Xudong Chen, Bruno Sinopoli
https://arxiv.org/abs/2508.21299 https://arxiv.org/pdf/2508.…

On Zero-sum Game Representation for Replicator Dynamics
Replicator dynamics have widely been used in evolutionary game theory to model how strategy frequencies evolve over time in large populations. The so-called payoff matrix encodes the pairwise fitness that each strategy obtains when interacting with every other strategy, and it solely determines the replicator dynamics. If the payoff matrix is unknown, we show in this paper that it cannot be inferred from observed strategy frequencies alone -- distinct payoff matrices can induce the same replica…

Reputational Conservatism in Expert Advice
Georgy Lukyanov, Anna Vlasova
https://arxiv.org/abs/2509.04036 https://arxiv.org/pdf/2509.04036

Reputational Conservatism in Expert Advice
We study expert recommendations under career concerns in a continuous signal environment. An expert observes a private signal about a binary payoff and recommends risky or safe; recommendations and outcomes are public and affect reputation and implementation. Equilibrium advice follows a cutoff rule. Under a mild relative-diagnosticity condition, the cutoff increases with reputation (reputational conservatism); informativeness and priors lower the cutoff while stronger career concerns raise it.…

Crosslisted article(s) found for cs.FL. https://arxiv.org/list/cs.FL/new
[1/1]:
- Mean-payoff and Energy Discrete Bidding Games
Guy Avni, Suman Sadhukhan
https://…

Semiparametric Identification of the Discount Factor and Payoff Function in Dynamic Discrete Choice Models
Yu Hao, Hiroyuki Kasahara, Katsumi Shimotsu
https://arxiv.org/abs/2507.19814

Semiparametric Identification of the Discount Factor and Payoff Function in Dynamic Discrete Choice Models
This paper investigates how the discount factor and payoff functions can be identified in stationary infinite-horizon dynamic discrete choice models. In single-agent models, we show that common nonparametric assumptions on per-period payoffs -- such as homogeneity of degree one, monotonicity, concavity, zero cross-differences, and complementarity -- provide identifying restrictions on the discount factor. These restrictions take the form of polynomial equalities and inequalities with degrees bo…

Mean-payoff and Energy Discrete Bidding Games
Guy Avni, Suman Sadhukhan
https://arxiv.org/abs/2509.00506 https://arxiv.org/pdf/2509.00506

Mean-payoff and Energy Discrete Bidding Games
A \emph{bidding} game is played on a graph as follows. A token is placed on an initial vertex and both players are allocated budgets. In each turn, the players simultaneously submit bids that do not exceed their available budgets, the higher bidder moves the token, and pays the bid to the lower bidder. We focus on \emph{discrete}-bidding, which are motivated by practical applications and restrict the granularity of the players' bids, e.g, bids must be given in cents. We study, for the first tim…

Tom Lehrer wasn't just a satirist or a musician. He as a comedian who could quietly tell a joke and wait more than SIXTY YEARS for the payoff.
That's dedication to craft.
We lost an icon.
From:
https://bsky.app/profile/opalescentopa

Co-Investment with Payoff-Sharing Mechanism for Cooperative Decision-Making in Network Design Games
Mingjia He, Andrea Censi, Emilio Frazzoli, Gioele Zardini
https://arxiv.org/abs/2508.12059

Co-Investment with Payoff-Sharing Mechanism for Cooperative Decision-Making in Network Design Games
Network-based systems are inherently interconnected, with the design and performance of subnetworks being interdependent. However, the decisions of self-interested operators may lead to suboptimal outcomes for users and the overall system. This paper explores cooperative mechanisms that can simultaneously benefit both operators and users. We address this challenge using a game-theoretical framework that integrates both non-cooperative and cooperative game theory. In the non-cooperative stage, w…

Having a consultant congratulate you, because the project is so clean, up to date and well tested is quite a payoff for fighting to get the time to properly test and update it

Two-Person Additively-Separable Sum Games
Somdeb Lahiri
https://arxiv.org/abs/2507.19325 https://arxiv.org/pdf/2507.19325

Two-Person Additively-Separable Sum Games
We consider a subclass of bimatrix games which we refer to as two person additively separable sum games, where the sum of the payoffs of the two players is additively separable. The payoff to the row player at each pair of pure strategies, is the sum of two numbers, the first of which may be dependent on the pure strategy chosen by the column player and the second being independent of the pure strategy chosen by the column player. The payoff to the column player at each pair of pure strategies,…

Empirical Analysis of the Model-Free Valuation Approach: Hedging Gaps, Conservatism, and Trading Opportunities
Zixing Chen, Yihan Qi, Shanlan Que, Julian Sester, Xiao Zhang
https://arxiv.org/abs/2508.16595

Empirical Analysis of the Model-Free Valuation Approach: Hedging Gaps, Conservatism, and Trading Opportunities
In this paper we study the quality of model-free valuation approaches for financial derivatives by systematically evaluating the difference between model-free super-hedging strategies and the realized payoff of financial derivatives using historical option prices from several constituents of the S&P 500 between 2018 and 2022. Our study allows in particular to describe the realized gap between payoff and model-free hedging strategy empirically so that we can quantify to which degree model-free…

Probabilistic closed-form formulas for pricing nonlinear payoff variance and volatility derivatives under Schwartz model with time-varying log-return volatility
Nontawat Bunchak, Udomsak Rakwongwan, Phiraphat Sutthimat
https://arxiv.org/abs/2506.15386

Probabilistic closed-form formulas for pricing nonlinear payoff variance and volatility derivatives under Schwartz model with time-varying log-return volatility
This paper presents closed-form analytical formulas for pricing volatility and variance derivatives with nonlinear payoffs under discrete-time observations. The analysis is based on a probabilistic approach assuming that the underlying asset price follows the Schwartz one-factor model, where the volatility of log-returns is time-varying. A difficult challenge in this pricing problem is to solve an analytical formula under the assumption of time-varying log-return volatility, resulting in the re…

Learning in Repeated Multi-Objective Stackelberg Games with Payoff Manipulation
Phurinut Srisawad, Juergen Branke, Long Tran-Thanh
https://arxiv.org/abs/2508.14705 https://

Learning in Repeated Multi-Objective Stackelberg Games with Payoff Manipulation
We study payoff manipulation in repeated multi-objective Stackelberg games, where a leader may strategically influence a follower's deterministic best response, e.g., by offering a share of their own payoff. We assume that the follower's utility function, representing preferences over multiple objectives, is unknown but linear, and its weight parameter must be inferred through interaction. This introduces a sequential decision-making challenge for the leader, who must balance preference elicita…

Measuring Informativeness Gap of (Mis)Calibrated Predictors
Yiding Feng, Wei Tang
https://arxiv.org/abs/2507.12094 https://arxiv.org/…

Measuring Informativeness Gap of (Mis)Calibrated Predictors
In many applications, decision-makers must choose between multiple predictive models that may all be miscalibrated. Which model (i.e., predictor) is more "useful" in downstream decision tasks? To answer this, our first contribution introduces the notion of the informativeness gap between any two predictors, defined as the maximum normalized payoff advantage one predictor offers over the other across all decision-making tasks. Our framework strictly generalizes several existing notions: it subsu…

Aligning Large Language Model Agents with Rational and Moral Preferences: A Supervised Fine-Tuning Approach
Wei Lu, Daniel L. Chen, Christian B. Hansen
https://arxiv.org/abs/2507.20796

Aligning Large Language Model Agents with Rational and Moral Preferences: A Supervised Fine-Tuning Approach
Understanding how large language model (LLM) agents behave in strategic interactions is essential as these systems increasingly participate autonomously in economically and morally consequential decisions. We evaluate LLM preferences using canonical economic games, finding substantial deviations from human behavior. Models like GPT-4o show excessive cooperation and limited incentive sensitivity, while reasoning models, such as o3-mini, align more consistently with payoff-maximizing strategies. …

Replaced article(s) found for cs.DS. https://arxiv.org/list/cs.DS/new
[1/1]:
- An Objective Improvement Approach to Solving Discounted Payoff Games
Daniele Dell'Erba, Arthur Dumas, Sven Schewe

Unbeatable imitation of a friend
Masahiko Ueda
https://arxiv.org/abs/2507.16221 https://arxiv.org/pdf/2507.16221

Unbeatable imitation of a friend
Imitation sometimes achieves success in multi-agent situations even though it is very simple. In game theory, success of imitation has been characterized by unbeatability against other agents. Previous studies specified conditions under which imitation is unbeatable in repeated games, and clarified that the existence of unbeatable imitation is strongly related to the existence of payoff-controlling strategies, called zero-determinant strategies. However, the previous studies mainly focused on `…

Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework
Michael Ledford, William Regli
https://arxiv.org/abs/2506.15856 …

Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework
Cooperative multi-agent systems often face tasks that require coordinated actions under uncertainty. While multi-armed bandit (MAB) problems provide a powerful framework for decentralized learning, most prior work assumes individually attainable rewards. We address the challenging setting where rewards are threshold-activated: an arm yields a payoff only when a minimum number of agents pull it simultaneously, with this threshold unknown in advance. Complicating matters further, some arms are de…

Two-Person Cooperative Games with delta-Rationality
Fang-Fang Tang, Yongsheng Xu
https://arxiv.org/abs/2506.16465 https://arxiv.org/p…

Two-Person Cooperative Games with delta-Rationality
A player's payoff is modeled as consisting of two parts: a rational-value part and a distortion-value part. It is argued that the (total) payoff function should be used to explain and predict the behaviors of the players, while the rational value function should be used to conduct welfare analysis of the final outcome. We use the Nash demand game to illustrate our model.

ACE: Automated Technical Debt Remediation with Validated Large Language Model Refactorings
Adam Tornhill, Markus Borg, Nadim Hagatulah, Emma S\"oderberg
https://arxiv.org/abs/2507.03536

ACE: Automated Technical Debt Remediation with Validated Large Language Model Refactorings
The remarkable advances in AI and Large Language Models (LLMs) have enabled machines to write code, accelerating the growth of software systems. However, the bottleneck in software development is not writing code but understanding it; program understanding is the dominant activity, consuming approximately 70% of developers' time. This implies that improving existing code to make it easier to understand has a high payoff and - in the age of AI-assisted coding - is an essential activity to ensure…

Can Limited Liability Increase Stability for Banks: A Dynamic Portfolio Approach
Deb Narayan Barik, Siddhartha P. Chakrabarty
https://arxiv.org/abs/2507.16494 https://

Can Limited Liability Increase Stability for Banks: A Dynamic Portfolio Approach
We present a novel approach for the bank's decision problem, incorporating Limited Liability in the objective function. Accordingly, we consider continuous time models, with and without Limited Liability. We compare the solutions of these two models to demonstrate the effect of inclusion of Limited Liability. To solve the problem with the objective function incorporating Limited Liability, we approximate the payoff function to another set of functions for which we have closed-form solutions. Th…

Thresholds for sensitive optimality and Blackwell optimality in stochastic games
St\'ephane Gaubert, Julien Grand-Cl\'ement, Ricardo D. Katz
https://arxiv.org/abs/2506.18545

Thresholds for sensitive optimality and Blackwell optimality in stochastic games
We investigate refinements of the mean-payoff criterion in two-player zero-sum perfect-information stochastic games. A strategy is Blackwell optimal if it is optimal in the discounted game for all discount factors sufficiently close to $1$. The notion of $d$-sensitive optimality interpolates between mean-payoff optimality (corresponding to the case $d=-1$) and Blackwell optimality ($d=+\infty$). The Blackwell threshold $α_{\sf Bw} \in [0,1[$ is the discount factor above which all optimal strat…

Convergence Rate of Generalized Nash Equilibrium Learning in Strongly Monotone Games with Linear Constraints
Tatiana Tatarenko, Maryam Kamgarpour
https://arxiv.org/abs/2507.12112 …

Convergence Rate of Generalized Nash Equilibrium Learning in Strongly Monotone Games with Linear Constraints
We consider payoff-based learning of a generalized Nash equilibrium (GNE) in multi-agent systems. Our focus is on games with jointly convex constraints of a linear structure and strongly monotone pseudo-gradients. We present a convergent procedure based on a partial regularization technique and establish the convergence rate of its iterates under one- and two-point payoff-based feedback. To the best of our knowledge, this work is the first one characterizing the convergence speed of iterates to…

Stable and Fair Benefit Allocation in Mixed-Energy Truck Platooning: A Coalitional Game Approach
Ting Bai, Karl Henrik Johansson, Jonas M{\aa}rtensson, Andreas A. Malikopoulos
https://arxiv.org/abs/2507.16923

Stable and Fair Benefit Allocation in Mixed-Energy Truck Platooning: A Coalitional Game Approach
This paper addresses the benefit allocation in a mixed-energy truck platoon composed of fuel-powered and electric trucks. The interactions among trucks during platoon formation are modeled as a coalitional game with transferable utility. We first design a stable payoff allocation scheme that accounts for truck heterogeneity in energy savings and platoon roles (leader or follower), establishing core-stability conditions to ensure that no subset of trucks has an incentive to deviate for greater b…

Dependence bounds for the difference of stop-loss payoffs on the difference of two random variables
Hamza Hanbali, Jan Dhaene, Daniel Linders
https://arxiv.org/abs/2508.12606 ht…

Dependence bounds for the difference of stop-loss payoffs on the difference of two random variables
This paper considers the difference of stop-loss payoffs where the underlying is a difference of two random variables. The goal is to study whether the comonotonic and countermonotonic modifications of those two random variables can be used to construct upper and lower bounds for the expected payoff, despite the fact that the payoff function is neither convex nor concave. The answer to the central question of the paper requires studying the crossing points of the cdf of the original difference …

Risky Advice and Reputational Bias
Georgy Lukyanov, Anna Vlasova, Maria Ziskelevich
https://arxiv.org/abs/2508.19707 https://arxiv.org/pdf/2508.19707

Risky Advice and Reputational Bias
We study expert advice under reputational incentives, with sell-side equity research as the lead application. A long-lived analyst receives a continuous private signal about a binary payoff and recommends a risky (Buy) or safe action. Recommendations and outcomes are public, and clients' implementation effort depends on current reputation. In a recursive, belief-based equilibrium: (i) advice follows a cutoff in the signal; (ii) under a simple diagnosticity asymmetry, the cutoff is (weakly) incr…

You know what's the difference between a human programmer and an "#AI coding assistant"?
Sure, human programmers make mistakes. And rookies often make "worse" mistakes than an #LLM can come up with. However, the difference is that humans can actually learn. Teaching them comes with a payoff; not always and not necessarily for your project, but there's a good chance that they'll become better programmers and contribute back to the community.
Sure, human programmers sometimes plagiarize. And of course they need to look at some code while they learn. However, they actually can think on their own and come up with something original. And they can learn that plagiarism is wrong.
And most importantly, usually they don't lie if they don't have to, and there are limits to their smugness. You can build a healthy community with them.
You can't build a community with unethical bullshit-spitting machines.
#programming #FreeSoftware #OpenSource

Replaced article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- Learning in Repeated Multi-Objective Stackelberg Games with Payoff Manipulation
Phurinut Srisawad, Juergen Branke, Long Tran-Thanh

Durable Goods Monopoly with Free Disposal: A Folk Theorem
Zihao Li
https://arxiv.org/abs/2507.13137 https://arxiv.org/pdf/2507.13137

Durable Goods Monopoly with Free Disposal: A Folk Theorem
We study a model of dynamic monopoly with differentiated goods that buyers can freely dispose of. The model extends the framework of Coasian bargaining to situations in which the quantity or quality of the good is endogenously determined. Our main result is that when players are patient, the seller can sustain in equilibrium any payoff between the lowest possible buyer valuation and (approximately) the highest payoff achievable with commitment power, thus establishing a folk theorem. We apply o…

Coordinating cooperation in stag-hunt game: Emergence of evolutionarily stable procedural rationality
Joy Das Bairagya, Sagar Chakraborty
https://arxiv.org/abs/2508.08301 https:…

Coordinating cooperation in stag-hunt game: Emergence of evolutionarily stable procedural rationality
Humans are bounded rational at best and this, we argue, has worked in their favour in the hunter-gatherer society where emergence of a coordinated action, leading to cooperation, is otherwise the standard stag-hunt dilemma (when individuals are rational). In line with the fact the humans strive for developing self-reputation by having less propensity to cheat than to be cheated, we observe that the payoff structure of the stag-hunt game appropriately modifies to that of coordination-II game. Su…

Network Heterogeneity and Value of Information
Kota Murayama
https://arxiv.org/abs/2506.17660 https://arxiv.org/pdf/2506.17660…

Network Heterogeneity and Value of Information
This paper studies how payoff heterogeneity affects the value of information in beauty contest games. I show that public information provision is detrimental to welfare if and only if agents' Katz-Bonacich centralities exhibit specific forms of heterogeneity, stemming from the network of coordination motives. A key insight is that agents may value the commonality of information so differently that some are harmed by their neighbors knowing what others know. Leveraging this insight, I also show …

{\epsilon}-Stationary Nash Equilibria in Multi-player Stochastic Graph Games
Ali Asadi, L\'eonard Brice, Krishnendu Chatterjee, K. S. Thejaswini
https://arxiv.org/abs/2508.15356

ε-Stationary Nash Equilibria in Multi-player Stochastic Graph Games
A strategy profile in a multi-player game is a Nash equilibrium if no player can unilaterally deviate to achieve a strictly better payoff. A profile is an $ε$-Nash equilibrium if no player can gain more than $ε$ by unilaterally deviating from their strategy. In this work, we use $ε$-Nash equilibria to approximate the computation of Nash equilibria. Specifically, we focus on turn-based, multiplayer stochastic games played on graphs, where players are restricted to stationary strategies -- str…

Reasoning about Bounded Reasoning
Shuige Liu, Gabriel Ziegler
https://arxiv.org/abs/2506.19737 https://arxiv.org/pdf/2506.19737

Reasoning about Bounded Reasoning
Interactive decision-making relies on strategic reasoning. Two prominent frameworks are (1) models of bounded reasoning, exemplified by level-$k$ models, which keep reasoning implicit, and (2) epistemic game theory, which makes reasoning explicit. We connect these approaches by "lifting" static complete-information games into incomplete-information settings where payoff types reflect players' reasoning depths as in level-$k$ models. We introduce downward rationalizability, defined via minimal b…

Resource-Splitting Games with Tullock-Based Lossy Contests
Marko Maljkovic, Gustav Nilsson, Nikolas Geroliminis
https://arxiv.org/abs/2507.13853 https://…

Resource-Splitting Games with Tullock-Based Lossy Contests
This paper introduces a novel class of multi-stage resource allocation games that model real-world scenarios in which profitability depends on the balance between supply and demand, and where higher resource investment leads to greater returns. Our proposed framework, which incorporates the notion of profit loss due to insufficient player participation, gives rise to a Tullock-like functional form of the stage payoff structure when weighted fair proportional resource allocation is applied. We e…

Interim correlated rationalizability in large games
Lukasz Balbus, Michael Greinecker, Kevin Reffett, Lukasz Wozny
https://arxiv.org/abs/2506.18426 https:/…

Interim correlated rationalizability in large games
We provide general theoretical foundations for modeling strategic uncertainty in large distributional Bayesian games with general type spaces, using a version of interim correlated rationalizability. We then focus on the case in which payoff functions are supermodular in actions, as is common in the literature on global games. This structure allows us to identify extremal interim correlated rationalizable solutions with extremal interim Bayes-Nash equilibria. Notably, no order structure on type…

Value of History in Social Learning: Applications to Markets for History
Hiroto Sato, Konan Shimizu
https://arxiv.org/abs/2507.11029 https://

Value of History in Social Learning: Applications to Markets for History
In social learning environments, agents acquire information from both private signals and the observed actions of predecessors, referred to as history. We define the value of history as the gain in expected payoff from accessing both the private signal and history, compared to relying on the signal alone. We first characterize the information structures that maximize this value, showing that it is highest under a mixture of full information and no information. We then apply these insights to a …

The asymmetrical Acquisition of information about the range of asset value in market
Jianhao Su, Yanliang Zhang
https://arxiv.org/abs/2508.09615 https://ar…

The asymmetrical Acquisition of information about the range of asset value in market
The information investors acquire in asset markets has various forms. We refer to range information as information about the upper and lower bound which the payoff of an asset may reach in the future. This paper explores the market impacts of investors' asymmetrical acquisition of range information. Uninformed traders are inherently unable to directly obtain the private signal held by informed traders. This study shows that when range information is released to investors asymmetrically, uninfor…