Tootfinder

Raiders' Contender for Comeback Player of the Year https://www.si.com/nfl/raiders/las-vegas-maxx-crosby-pro-bowl-pete-carroll

Deciding the Value of Two-Clock Almost Non-Zeno Weighted Timed Games
Isa Vialard
https://arxiv.org/abs/2508.00014 https://arxiv.org/pdf/2508.00014

Deciding the Value of Two-Clock Almost Non-Zeno Weighted Timed Games
The Value Problem for weighted timed games (wtgs) consists in determining, given a two-player weighted timed game with a reachability objective and a rational threshold, whether or not the value of the game exceeds the threshold. When restrained to wtgs with non-negative weight, this problem is known to be undecidable for weighted timed games with three or more clocks, and decidable for one-clock wtgs. The Value Problem for two-clock non-negative wtgs, which remained stubbornly open for a decad…

Sources detail EA's issues developing the next Battlefield, which now has a $400M budget; some staff were skeptical of the EA leadership's 100M player target (Samuel Axon/Ars Technica)
https://arstechnica.com/gaming/2025/07

What’s wrong with AAA games? The development of the next Battlefield has answers.
EA insiders describe stress and setbacks in a project that’s too big to fail.

How LLMs are Shaping the Future of Virtual Reality
S\"ueda \"Ozkaya, Santiago Berrezueta-Guzman, Stefan Wagner
https://arxiv.org/abs/2508.00737 https://

How LLMs are Shaping the Future of Virtual Reality
The integration of Large Language Models (LLMs) into Virtual Reality (VR) games marks a paradigm shift in the design of immersive, adaptive, and intelligent digital experiences. This paper presents a comprehensive review of recent research at the intersection of LLMs and VR, examining how these models are transforming narrative generation, non-player character (NPC) interactions, accessibility, personalization, and game mastering. Drawing from an analysis of 62 peer reviewed studies published b…

NFL Week 1 injury report: Player statuses for all 16 games https://www.nfl.com/news/nfl-week-1-injury-report-player-statuses-for-all-16-games-2025-season

»Solo RPGs: A Breakdown of Single Player Role-Playing Games«
You don't always have to be online or watch TV to entertain yourself ;)
🎲 https://wizardsrespite.com/2024/02/13/solo-rpgs-a-breakdown-of-single-player-role-playi…

Solo RPGs: A Breakdown of Single Player Role-Playing Games - Wizard's Respite
Take a close look at the solo RPGs. Discover their history, how they evolved over the years, and what they are today.

So arguably the Pac-Man ghost logic is the exact opposite of “AI”.
It’s extremely well defined behavior based on very basic deterministic algorithms that are so simple a 8-year old player can understand them and anticipate them correctly for those high-scores.
The game actually is famous for the simple enemy logic and studied by games designers for it.
Pac-Man enemy behavior:
deterministic, well-defined algorithm that can easily be executed on the most primitive* computer hardware
“AI”:
black-box algorithm with indeterministic behavior that requires a metric shitload of compute
—
*By “primitive computer hardware” I mean that the Pac-Man arcade machine runs on a Zilog Z80 CPU with 8,500 transistors.The CPU in the phone you are reading this on has (latest iPhone as example) 15 billion transistors or so (almost 2 million times more) and runs tens of thousands of times faster.

Mean Field Games of Controls with Dirichlet \& Neumann Boundary Conditions
P. Jameson Graber, Kyle Rosengartner
https://arxiv.org/abs/2508.21642 https://

Mean Field Games of Controls with Dirichlet \& Neumann Boundary Conditions
In a mean field game of controls, a large population of identical players seek to minimize a cost that depends on the joint distribution of the states of the players and their controls. We consider the classes of mean field games of controls in which the value function and the distribution of player states satisfy either Dirichlet or Neumann boundary conditions. We prove that such systems are well-posed either with sufficient smallness conditions or in the case of monotone couplings.

Maker playing against an invisible Breaker
Dennis Clemens, Fabian Hamann, Mirjana Mikala\v{c}ki, Yannick Mogge, Milo\v{s} Stojakovi\'c
https://arxiv.org/abs/2507.22519 https…

Maker playing against an invisible Breaker
We initiate the study of the phantom version of Maker-Breaker positional games. In a phantom game, the moves of one of the players are hidden from the other player, who still has the complete information. We look at the biased $(a:b)$ Maker-PhantomBreaker games where the board is the edge set of the complete graph on $n$ vertices, $K_n$, and Maker has no information about PhantomBreaker's choices of edges. We give randomized strategies for both players in four classical games: connectivity game…

Absolutely the most surprising part of this obit of Dilip Doshi, a former Indian #cricket player, is that while Doshi always struck me as the squarest of blokes, he was thick chums with MICK JAGGER, the sultan of cool.

The Effect of Network Topology on the Equilibria of Influence-Opinion Games
Yigit Ege Bayiz, Arash Amini, Radu Marculescu, Ufuk Topcu
https://arxiv.org/abs/2506.22293

The Effect of Network Topology on the Equilibria of Influence-Opinion Games
Online social networks exert a powerful influence on public opinion. Adversaries weaponize these networks to manipulate discourse, underscoring the need for more resilient social networks. To this end, we investigate the impact of network connectivity on Stackelberg equilibria in a two-player game to shape public opinion. We model opinion evolution as a repeated competitive influence-propagation process. Players iteratively inject \textit{messages} that diffuse until reaching a steady state, mo…

Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games
Ant\'onio Afonso, Iolanda Leite, Alessandro Sestini, Florian Fuchs, Konrad Tollmar, Linus Gissl\'en
https://arxiv.org/abs/2506.23626

Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games
Reinforcement Learning (RL) in games has gained significant momentum in recent years, enabling the creation of different agent behaviors that can transform a player's gaming experience. However, deploying RL agents in production environments presents two key challenges: (1) designing an effective reward function typically requires an RL expert, and (2) when a game's content or mechanics are modified, previously tuned reward weights may no longer be optimal. Towards the latter challenge, we prop…

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,…

Sensitivity-Driven Migration and the Evolution of Cooperation in Multi-Player Games on Structured Populations
Dhaker Kroumi
https://arxiv.org/abs/2509.01126 https://

Sensitivity-Driven Migration and the Evolution of Cooperation in Multi-Player Games on Structured Populations
Cooperation often depends on individuals avoiding exploitation and interacting preferentially with other cooperators. We explore how context-dependent migration influences the evolution of cooperation in spatially structured populations. Individuals interact in small groups through public goods games and reproduce with possible dispersal. Cooperators migrate more frequently when surrounded by defectors, while defectors disperse uniformly. This behavioral asymmetry reflects realistic differences…

Learning with Episodic Hypothesis Testing in General Games: A Framework for Equilibrium Selection
Ruifan Yang, Manxi Wu
https://arxiv.org/abs/2507.23149 https://

Learning with Episodic Hypothesis Testing in General Games: A Framework for Equilibrium Selection
We introduce a new hypothesis testing-based learning dynamics in which players update their strategies by combining hypothesis testing with utility-driven exploration. In this dynamics, each player forms beliefs about opponents' strategies and episodically tests these beliefs using empirical observations. Beliefs are resampled either when the hypothesis test is rejected or through exploration, where the probability of exploration decreases with the player's (transformed) utility. In general fin…

Optimal Strategies to Catch Randomly Walking Cat
R\"udiger Jehn
https://arxiv.org/abs/2508.18276 https://arxiv.org/pdf/2508.18276

Optimal Strategies to Catch Randomly Walking Cat
The optimal strategies to catch a randomly walking cat in various environments are presented. All games have a player that opens a box at step $i$. If the cat is in this box the player wins, if not, the cat moves randomly to an adjacent box, or in case the box is open to the outside, the cat may escape. If the cat is not escaping, the next step of the game is played. In case the cat has doors to escape, the optimal strategy is determined that minimizes the escape chances of the cat. If there ar…

Viewfinder (Multi, XPd on PC) Inside a "holodeck" of some kind, use photos, paintings, screenshots, etc to change the world you're exploring, while looking for the much needed research to fix the outside world.
Finally something other than a sim game, lol. This is a really good puzzle adventure/walking.. sim 🤣 with a really neat hook. Any picture you can pick up (and later take) you can "plant" in the scene to alter the world, allowing you to solve the puzzles a…

ChatGPT (cat, I farted, to the French) can't beat the world's best chess player, and it sucks at old video games, mainly because ChatGPT is NOT INTELLIGENCE of ANY kind. It's a parrot machine.

Team Variance Optimization of n-Player Stochastic Games with Separately Controlled Chains
Li Xia
https://arxiv.org/abs/2507.22335 https://arxiv.org/pdf/250…

Team Variance Optimization of n-Player Stochastic Games with Separately Controlled Chains
In this paper, we study a subclass of n-player stochastic games, in which each player has their own internal state controlled only by their own action and their objective is a common goal called team variance which measures the total variation of the random rewards of all players. It is assumed that players cannot observe each others' state/action. Thus, players' internal chains are controlled separately by their own action and they are coupled through the objective of team variance. Since the …

The Cowboys' 2025 season hinges on 1 player: Dak Prescott https://insidethestar.com/the-cowboys-2025-season-hinges-on-1-player-dak-prescott

Quantitative convergence for displacement monotone Mean Field Games of control
Joe Jackson, Alp\'ar R. M\'esz\'aros
https://arxiv.org/abs/2507.17014 https://

Quantitative convergence for displacement monotone Mean Field Games of control
In this paper we establish quantitative convergence results for both open and closed-loop Nash equilibria of N-player stochastic differential games in the setting of Mean Field Games of Controls (MFGC), a class of models where interactions among agents occur through both states and controls. Our analysis covers a general class of non-separable Hamiltonians satisfying a displacement monotonicity condition, along with mild regularity and growth conditions at infinity. A major novelty of our work …

Mario Kart 7: back online
With the help of the Pretendo network, I've managed to have a few games of this online over the past week or so, as well as doing some more time trials. The lobbies aren't full, but any stretch, but even when there's only three people in a race the catch up algorithms mean that it's fun to compete. On a couple of occasions there was one player who knew glitches on levels which meant they won easily, but they never stayed online for long.
…

Stochastic Graphon Games with Interventions
Eyal Neuman, Sturmius Tuschmann
https://arxiv.org/abs/2507.00561 https://arxiv.org/pdf/25…

Stochastic Graphon Games with Interventions
We consider a class of targeted intervention problems in dynamic network and graphon games. First, we study a general dynamic network game in which players interact over a graph and maximize their heterogeneous, concave goal functionals, which depend on both their own actions and their interactions with their neighbors. We establish the existence and uniqueness of the Nash equilibrium in both the finite-player network game and the corresponding infinite-player graphon game. We also prove the co…

Where are the Frontlines? A Visualization Approach for Map Control in Team-Based Games
Jonas Pech\'e, Aliaksei Tsishurou, Alexander Zap, Guenter Wallner
https://arxiv.org/abs/2507.19193

Where are the Frontlines? A Visualization Approach for Map Control in Team-Based Games
A central area of interest in many competitive online games is spatial behavior which due to its complexity can be difficult to visualize. Such behaviors of interest include not only overall movement patterns but also being able to understand which player or team is exerting control over an area to inform decision-making. Map control can, however, be challenging to quantify. In this paper, we propose a method for calculating frontlines and first efforts towards a visualization of them. The visu…

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.

I have not played Remtach. This review is really interesting describing this as a team fighting game with soccer as more of a theme. And for the moment to moment game play that sounds great.
But it is funny that in another way that's just soccer. TBH this game is way more soccer then FIFA is where you control a whole team.
Personally I don't love these multiplayer games. I could like this with a single player mode and imagine doing a whole career!

Limit-Computable Grains of Truth for Arbitrary Computable Extensive-Form (Un)Known Games
Cole Wyeth, Marcus Hutter, Jan Leike, Jessica Taylor
https://arxiv.org/abs/2508.16245 ht…

Limit-Computable Grains of Truth for Arbitrary Computable Extensive-Form (Un)Known Games
A Bayesian player acting in an infinite multi-player game learns to predict the other players' strategies if his prior assigns positive probability to their play (or contains a grain of truth). Kalai and Lehrer's classic grain of truth problem is to find a reasonably large class of strategies that contains the Bayes-optimal policies with respect to this class, allowing mutually-consistent beliefs about strategy choice that obey the rules of Bayesian inference. Only small classes are known to ha…

Doing calculus and checking my results with o3 feels a lot like Jernau Gurgeh talking to the ship about the progress of his game in Player of Games.

Hybrid Game Control Envelope Synthesis
Aditi Kabra, Jonathan Laurent, Stefan Mitsch, Andr\'e Platzer
https://arxiv.org/abs/2508.05997 https://arxiv.org…

Hybrid Game Control Envelope Synthesis
Control problems for embedded systems like cars and trains can be modeled by two-player hybrid games. Control envelopes, which are families of safe control solutions, correspond to nondeterministic winning policies of hybrid games, where each deterministic specialization of the policy is a control solution. This paper synthesizes nondeterministic winning policies for hybrid games that are as permissive as possible. It introduces subvalue maps, a compositional representation of such policies tha…

Approximating fixed size quantum correlations in polynomial time
Julius A. Zeiss, Gereon Ko{\ss}mann, Omar Fawzi, Mario Berta
https://arxiv.org/abs/2507.12302

Approximating fixed size quantum correlations in polynomial time
We show that $\varepsilon$-additive approximations of the optimal value of fixed-size two-player free games with fixed-dimensional entanglement assistance can be computed in time $\mathrm{poly}(1/\varepsilon)$. This stands in contrast to previous analytic approaches, which focused on scaling with the number of questions and answers, but yielded only strict $\mathrm{exp}(1/\varepsilon)$ guarantees. Our main result is based on novel Bose-symmetric quantum de Finetti theorems tailored for constrai…

Finite-Horizon Partially Observable Semi-Markov Games with Risk Probability Criteria
Xin Wen, Li Xia, Zhihui Yu
https://arxiv.org/abs/2508.17791 https://ar…

Finite-Horizon Partially Observable Semi-Markov Games with Risk Probability Criteria
This paper studies partially observable two-person zero-sum semi-Markov games under a probability criterion, in which the system state may not be completely observed. It focuses on the probability that the accumulated rewards of player 1 (i.e., the incurred costs of player 2) fall short of a specified target at the terminal stage, which represents the risk of player 1 and the capacity of player 2. We study the game model via the technology of augmenting state space with the joint conditional di…

Some intermittent thoughts about 4E as I review it after not having run a game in like 8 years.
1. going from playing almost entirely super rules light NSR games to this has made me greatly underestimate how much prep is involved.
2. I'm also a lot worried about teaching new people this.
3. I don't like what they did about alignment, but I never liked D&D alignment. I do like the deieties as a shorthand for the player's values and I like the amount of emphas…

Slavic Techniques for Hat Guessing Algorithms
I. M. J. McInnis
https://arxiv.org/abs/2507.21487 https://arxiv.org/pdf/2507.21487

Slavic Techniques for Hat Guessing Algorithms
2023 undergraduate thesis on a deterministic "hat game." For a digraph $D$, each player stands on a vertex $v$, is assigned a hat from $h(v)$ possible colors, and makes $g(v)$ guesses of her hat's color based on her out-neighbors' hats. If there exists a collective strategy that guarantees a correct guess for any hat assignment, the game is winnable. Which games $(D,g,h)$ are winnable? Two much-studied parameters: $μ(D)$ is the maximum integer $k$ such that $(D,1,k)$ is winnable, and $\hatμ(D…

Using Generative AI to Uncover What Drives Player Enjoyment in PC and VR Games
Hisham Abdelqader
https://arxiv.org/abs/2508.16596 https://arxiv.org/pdf/250…

Using Generative AI to Uncover What Drives Player Enjoyment in PC and VR Games
As video games continue to evolve, understanding what drives player enjoyment remains a key challenge. Player reviews provide valuable insights, but their unstructured nature makes large-scale analysis difficult. This study applies generative AI and machine learning, leveraging Microsoft Phi-4 LLM and XGBoost, to quantify and analyze game reviews from Steam and Meta Quest stores. The approach converts qualitative feedback into structured data, enabling comprehensive evaluation of key game desig…

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…

Raiders’ Contender for Comeback Player of the Year https://www.si.com/nfl/raiders/las-vegas-maxx-crosby-pro-bowl-pete-carroll

Solving Zero-Sum Convex Markov Games
Fivos Kalogiannis, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Ian Gemp, Georgios Piliouras
https://arxiv.org/abs/2506.16120

Solving Zero-Sum Convex Markov Games
We contribute the first provable guarantees of global convergence to Nash equilibria (NE) in two-player zero-sum convex Markov games (cMGs) by using independent policy gradient methods. Convex Markov games, recently defined by Gemp et al. (2024), extend Markov decision processes to multi-agent settings with preferences that are convex over occupancy measures, offering a broad framework for modeling generic strategic interactions. However, even the fundamental min-max case of cMGs presents signi…

Turnpike properties in linear quadratic Gaussian N-player differential games
Asaf Cohen, Jiamin Jian
https://arxiv.org/abs/2507.11632 https://

Turnpike properties in linear quadratic Gaussian N-player differential games
We consider the long-time behavior of equilibrium strategies and state trajectories in a linear quadratic $N$-player game with Gaussian initial data. By analyzing convergence toward the corresponding ergodic game, we establish exponential convergence estimates between the solutions of the finite-horizon Riccati system and the associated algebraic Riccati system arising in the ergodic setting. Building on these results, we prove the convergence of the time-averaged value function and derive a tu…

Democratizing Game Modding with GenAI: A Case Study of StarCharM, a Stardew Valley Character Maker
Hamid Zand Miralvand, Mohammad Ronagh Nikghalb, Mohammad Darandeh, Abidullah Khan, Ian Arawjo, Jinghui Cheng
https://arxiv.org/abs/2507.13951

Democratizing Game Modding with GenAI: A Case Study of StarCharM, a Stardew Valley Character Maker
Game modding offers unique and personalized gaming experiences, but the technical complexity of creating mods often limits participation to skilled users. We envision a future where every player can create personalized mods for their games. To explore this space, we designed StarCharM, a GenAI-based non-player character (NPC) creator for Stardew Valley. Our tool enables players to iteratively create new NPC mods, requiring minimal user input while allowing for fine-grained adjustments through u…

{\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…

Asymmetric Network Games: $\alpha$-Potential Function and Learning
Kiran Rokade, Adit Jain, Francesca Parise, Vikram Krishnamurthy, Eva Tardos
https://arxiv.org/abs/2508.06619 h…

Asymmetric Network Games: $α$-Potential Function and Learning
In a network game, players interact over a network and the utility of each player depends on his own action and on an aggregate of his neighbours' actions. Many real world networks of interest are asymmetric and involve a large number of heterogeneous players. This paper analyzes static network games using the framework of $α$-potential games. Under mild assumptions on the action sets (compact intervals) and the utility functions (twice continuously differentiable) of the players, we derive an…

Using Psychophysiological Insights to Evaluate the Impact of Loot Boxes on Arousal
Gianmarco Tedeschi, Rune Kristian Lundedal Nielsen, Paolo Burelli
https://arxiv.org/abs/2507.04906

Using Psychophysiological Insights to Evaluate the Impact of Loot Boxes on Arousal
This study investigates the psychophysiological effects of loot box interactions in video games and their potential similarities to those recorded during gambling interactions. Using electrodermal activity (EDA) measurements, the research examines player arousal during loot box interactions and explores the relationship between Internet Gaming Disorder (IGD) severity and loot box interactions from a psychophysiological perspective. The study employs a custom-designed game to control experimenta…

BSDE Approach for $\alpha$-Potential Stochastic Differential Games
Xin Guo, Xun Li, Liangquan Zhang
https://arxiv.org/abs/2507.13256 https://

BSDE Approach for $α$-Potential Stochastic Differential Games
In this paper, we examine a class of $α$-potential stochastic differential games with random coefficients via the backward stochastic differential equations (BSDEs) approach. Specifically, we show that the first and second order linear derivatives of the objective function for each player can be expressed through the corresponding first and second-order adjoint equations, which leads to rigorous estimates for $α$. We illustrate the dependence of $α$ on game characteristics through detailed a…

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…

Nash equilibria in semidefinite games and Lemke-Howson paths
Constantin Ickstadt, Thorsten Theobald, Elias Tsigaridas, Antonios Varvitsiotis
https://arxiv.org/abs/2506.11940

Nash equilibria in semidefinite games and Lemke-Howson paths
We consider an algorithmic framework for two-player non-zero-sum semidefinite games, where each player's strategy is a positive semidefinite matrix with trace one. We formulate the computation of Nash equilibria in such games as semidefinite complementarity problems and develop symbolic-numeric techniques to trace generalized Lemke-Howson paths. These paths generalize the piecewise affine-linear trajectories of the classical Lemke-Howson algorithm for bimatrix games, replacing them with nonline…

Infinite lexicographic products of positional objectives
Antonio Casares, Pierre Ohlmann, Micha{\l} Skrzypczak, Igor Walukiewicz
https://arxiv.org/abs/2506.14544

Infinite lexicographic products of positional objectives
This paper contributes to the study of positional determinacy of infinite duration games played on potentially infinite graphs. Recently, [Ohlmann, TheoretiCS 2023] established that positionality of prefix-independent objectives is preserved by finite lexicographic products. We propose two different notions of infinite lexicographic products indexed by arbitrary ordinals, and extend Ohlmann's result by proving that they also preserve positionality. In the context of one-player positionality, th…

Fair Contracts in Principal-Agent Games with Heterogeneous Types
Jakub T{\l}uczek, Victor Villin, Christos Dimitrakakis
https://arxiv.org/abs/2506.15887 ht…

Fair Contracts in Principal-Agent Games with Heterogeneous Types
Fairness is desirable yet challenging to achieve within multi-agent systems, especially when agents differ in latent traits that affect their abilities. This hidden heterogeneity often leads to unequal distributions of wealth, even when agents operate under the same rules. Motivated by real-world examples, we propose a framework based on repeated principal-agent games, where a principal, who also can be seen as a player of the game, learns to offer adaptive contracts to agents. By leveraging a …

Protocols for Verifying Smooth Strategies in Bandits and Games
Miranda Christ, Daniel Reichman, Jonathan Shafer
https://arxiv.org/abs/2507.10567 https://…

Protocols for Verifying Smooth Strategies in Bandits and Games
We study protocols for verifying approximate optimality of strategies in multi-armed bandits and normal-form games. As the number of actions available to each player is often large, we seek protocols where the number of queries to the utility oracle is sublinear in the number of actions. We prove that such verification is possible for sufficiently smooth strategies that do not put too much probability mass on any specific action. We provide protocols for verifying that a smooth policy for a mul…

Markov Perfect Equilibria in Discrete Finite-Player and Mean-Field Games
Felix H\"ofer, H. Mete Soner, Atilla Y{\i}lmaz
https://arxiv.org/abs/2507.04540

Markov Perfect Equilibria in Discrete Finite-Player and Mean-Field Games
We study dynamic finite-player and mean-field stochastic games within the framework of Markov perfect equilibria (MPE). Our focus is on discrete time and space structures without monotonicity. Unlike their continuous-time analogues, discrete-time finite-player games generally do not admit unique MPE. However, we show that uniqueness is remarkably recovered when the time steps are sufficiently small, and we provide examples demonstrating the necessity of this assumption. This result, established…

Value-Set Iteration: Computing Optimal Correlated Equilibria in Infinite-Horizon Multi-Player Stochastic Games
Jiarui Gan, Rupak Majumdar
https://arxiv.org/abs/2506.07186

Value-Set Iteration: Computing Optimal Correlated Equilibria in Infinite-Horizon Multi-Player Stochastic Games
We study the problem of computing optimal correlated equilibria (CEs) in infinite-horizon multi-player stochastic games, where correlation signals are provided over time. In this setting, optimal CEs require history-dependent policies; this poses new representational and algorithmic challenges as the number of possible histories grows exponentially with the number of time steps. We focus on computing $(ε, δ)$-optimal CEs -- solutions that achieve a value within $ε$ of an optimal CE, while al…

Coalitions on the Fly in Cooperative Games
Yao Zhang, Indrajit Saha, Zhaohong Sun, Makoto Yokoo
https://arxiv.org/abs/2507.11883 https://

Coalitions on the Fly in Cooperative Games
In this work, we examine a sequential setting of a cooperative game in which players arrive dynamically to form coalitions and complete tasks either together or individually, depending on the value created. Upon arrival, a new player as a decision maker faces two options: forming a new coalition or joining an existing one. We assume that players are greedy, i.e., they aim to maximize their rewards based on the information available at their arrival. The objective is to design an online value di…

Last-Iterate Convergence in Adaptive Regret Minimization for Approximate Extensive-Form Perfect Equilibrium
Hang Ren, Xiaozhen Sun, Tianzi Ma, Jiajia Zhang, Xuan Wang
https://arxiv.org/abs/2508.07699

Last-Iterate Convergence in Adaptive Regret Minimization for Approximate Extensive-Form Perfect Equilibrium
The Nash Equilibrium (NE) assumes rational play in imperfect-information Extensive-Form Games (EFGs) but fails to ensure optimal strategies for off-equilibrium branches of the game tree, potentially leading to suboptimal outcomes in practical settings. To address this, the Extensive-Form Perfect Equilibrium (EFPE), a refinement of NE, introduces controlled perturbations to model potential player errors. However, existing EFPE-finding algorithms, which typically rely on average strategy converge…

A New Three-Players Auction Bridge with Dynamic Opponents and Team Members
Sourish Sarkar, Aritrabha Majumdar, Moutushi Chatterjee
https://arxiv.org/abs/2508.05582 https://

A New Three-Players Auction Bridge with Dynamic Opponents and Team Members
This article presents a new three-player version of the bridge playing card game for the purpose of ending fixed partnerships so that the play can be more dynamic and flexible. By dynamically redefining team makeup in real time, this game design increases unpredictability and forces players to repeatedly update strategy. A novel scoring system is introduced to reduce biases present in conventional rule-based games by favoring fairness via reward systems that enforce tactical decision making and…

Maximizing Social Welfare with Side Payments
Ivan Geffner, Caspar Oesterheld, Vincent Conitzer
https://arxiv.org/abs/2508.07147 https://arxiv.org/pdf/2508.…

Maximizing Social Welfare with Side Payments
We examine normal-form games in which players may \emph{pre-commit} to outcome-contingent transfers before choosing their actions. In the one-shot version of this model, Jackson and Wilkie showed that side contracting can backfire: even a game with a Pareto-optimal Nash equilibrium can devolve into inefficient equilibria once unbounded, simultaneous commitments are allowed. The root cause is a prisoner's dilemma effect, where each player can exploit her commitment power to reshape the equilibri…

This https://arxiv.org/abs/2403.07932 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGT_…

Feint Behaviors and Strategies: Formalization, Implementation and Evaluation
Feint behaviors refer to a set of deceptive behaviors in a nuanced manner, which enable players to obtain temporal and spatial advantages over opponents in competitive games. Such behaviors are crucial tactics in most competitive multi-player games (e.g., boxing, fencing, basketball, motor racing, etc.). However, existing literature does not provide a comprehensive (and/or concrete) formalization for Feint behaviors, and their implications on game strategies. In this work, we introduce the firs…