arXiv research

Expands MFGs to handle real-world asymmetric multi-agent games efficiently.

Paper tackles multiplayer symmetric games, securing equal share for n players.

New game approximates mean curvature flow evolution.

Algorithm converges to Nash equilibria in competitive games.

Study on mean field games with singular controls and their applications.

Zero-sum games such as chess and poker are, abstractly, functions that evaluate pairs of agents, for example labeling them `winner' and `loser'. If the game is approximately transitive, then self-play generates sequences of agents of increasing strength. However, nontransitive games, such as rock-paper-scissors, can ex…

We consider a symmetric multi-players zero-sum game with two strategic variables. There are $n$ players, $n\geq 3$. Each player is denoted by $i$. Two strategic variables are $t_i$ and $s_i$, $i\in \{1, \dots, n\}$. They are related by invertible functions. Using the minimax theorem by \cite{sion} we will show that Nas…

Deep learning is built on the foundational guarantee that gradient descent on an objective function converges to local minima. Unfortunately, this guarantee fails in settings, such as generative adversarial nets, that exhibit multiple interacting losses. The behavior of gradient-based methods in games is not well under…

FGNNs improve game-playing AI by exploiting symmetries.

The paper reveals a spinning top geometry in real-world games.

This paper tackles learning Stackelberg equilibrium in asymmetric games efficiently from noisy samples.

New algorithm reduces online learning regret for bounded recall games.

Policy mirror ascent achieves Nash equilibrium in mean field games without a population generative model.

Develops a game-theoretic approach to solve SGEP efficiently.

Study examines strategic exit timing in uncertain competition.

Research tackles alliance formation in many-player zero-sum games, showing reinforcement learning fails but a contract mechanism can help.

New algorithm for solving minimax problems over distributions converges to Nash equilibrium.

We study the solution's existence for a generalized Dynkin game of switching type which is shown to be the natural representation for general defaultable OTC contract with contingent CSA. This is a theoretical counterparty risk mitigation mechanism that allows the counterparty of a general OTC contract to switch from z…

Despite the considerable success enjoyed by machine learning techniques in practice, numerous studies demonstrated that many approaches are vulnerable to attacks. An important class of such attacks involves adversaries changing features at test time to cause incorrect predictions. Previous investigations of this proble…

New NPG variants ensure parameter convergence in multi-agent learning.

This paper deals with a stochastic order-driven market model with waiting costs, for order books with heterogenous traders. Offer and demand of liquidity drives price formation and traders anticipate future evolutions of the order book. The natural framework we use is mean field game theory, a class of stochastic diffe…

New foundation for Shapley value immune to coalitional manipulations.

Constant and symmetric price impact functions, most commonly used in agent-based market modelling, are shown to give rise to paradoxical and inconsistent outcomes in the simplest case of arbitrage exploitation when open-hold-close actions are considered. The solution of the paradox lies in the non-constant nature of re…

Improved GAN training stability through tunable classification losses.

Paper presents content-based models for game recommendation in cold start scenarios.

In this work, we ask the following question: Can visual analogies, learned in an unsupervised way, be used in order to transfer knowledge between pairs of games and even play one game using an agent trained for another game? We attempt to answer this research question by creating visual analogies between a pair of game…

Potential games, originally introduced in the early 1990's by Lloyd Shapley, the 2012 Nobel Laureate in Economics, and his colleague Dov Monderer, are a very important class of models in game theory. They have special properties such as the existence of Nash equilibria in pure strategies. This note introduces graphical…

IGGP learns game rules from varying quality game play, finding no overall trend.

Market makers optimize bid/ask quotes under hidden Markov chain uncertainty.

In this paper we study continuous-time stochastic control problems with both monotone and classical controls motivated by the so-called public good contribution problem. That is the problem of n economic agents aiming to maximize their expected utility allocating initial wealth over a given time period between private …

We introduce a topological combinatorial game called the Region Smoothing Swap Game. The game is played on a game board derived from the connected shadow of a link diagram on a (possibly non-orientable) surface by smoothing at crossings. Moves in the game are performed on regions of the diagram and can switch the direc…

We present a new general board game (GBG) playing and learning framework. GBG defines the common interfaces for board games, game states and their AI agents. It allows one to run competitions of different agents on different games. It standardizes those parts of board game playing and learning that otherwise would be t…

Just as war is sometimes fallaciously represented as a zero sum game -- when in fact war is a negative sum game - stock market trading, a positive sum game over time, is often erroneously represented as a zero sum game. This is called the "zero sum fallacy" -- the erroneous belief that one trader in a stock market exch…

The existence of stationary Markov perfect equilibria in stochastic games is shown under a general condition called "(decomposable) coarser transition kernels". This result covers various earlier existence results on correlated equilibria, noisy stochastic games, stochastic games with finite actions and state-independe…

Game theory helps analyze ESOs/EBIs in production and service sectors.

Combinatorial two-player games have recently been applied to knot theory. Examples of this include the Knotting-Unknotting Game and the Region Unknotting Game, both of which are played on knot shadows. These are turn-based games played by two players, where each player has a separate goal to achieve in order to win the…

We start briefly surveying research on optimal stopping games since their introduction by E.B.Dynkin more than 40 years ago. Recent renewed interest to dynkin's games is due, in particular, to the study of Israeli (game) options introduced in 2000. We discuss the work on these options and related derivative securities …

The paper explores how regularization can lead to convergence in imperfect information games.

Educational game on crypto investment helps students grasp macroeconomics.

Simplified NFT games discussed with methods for extracting value.

We introduce TextWorld, a sandbox learning environment for the training and evaluation of RL agents on text-based games. TextWorld is a Python library that handles interactive play-through of text games, as well as backend functions like state tracking and reward assignment. It comes with a curated list of games whose …

Paper tackles hidden game problem in AI alignment and language games.

AEC Games model represents software MARL environments better than POSGs.

Gradient Descent Ascent converges to von-Neumann solution in hidden zero-sum games.

Generalizes region select game to $k$-colored knot diagrams.

We introduce CSE for MLSF games and devise online learning algorithms for achieving no-external Stackelberg-regret.

Deep Reinforcement Learning automates match-3 game testing.

Unified framework for Bayesian and Frequentist statistics.