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We present Pommerman, a multi-agent environment based on the classic console game Bomberman. Pommerman consists of a set of scenarios, each having at least four players and containing both cooperative and competitive aspects. We believe…

Multiagent Systems · Computer Science 2022-04-22 Cinjon Resnick , Wes Eldridge , David Ha , Denny Britz , Jakob Foerster , Julian Togelius , Kyunghyun Cho , Joan Bruna

The Pommerman simulation was recently developed to mimic the classic Japanese game Bomberman, and focuses on competitive gameplay in a multi-agent setting. We focus on the 2$\times$2 team version of Pommerman, developed for a competition at…

Machine Learning · Computer Science 2019-11-14 Hardik Meisheri , Omkar Shelke , Richa Verma , Harshad Khadilkar

Pommerman is a multi-agent environment that has received considerable attention from researchers in recent years. This environment is an ideal benchmark for multi-agent training, providing a battleground for two teams with communication…

Multiagent Systems · Computer Science 2025-01-09 Nhat-Minh Huynh , Hoang-Giang Cao , I-Chen Wu

In this paper, we study AI approaches to successfully play a 2-4 players, full information, Bomberman variant published on the CodinGame platform. We compare the behavior of three search algorithms: Monte Carlo Tree Search, Rolling Horizon…

Artificial Intelligence · Computer Science 2022-03-21 Dominik Kowalczyk , Jakub Kowalski , Hubert Obrzut , Michał Maras , Szymon Kosakowski , Radosław Miernik

The purpose of this tutorial is to help individuals use the \underline{FireCommander} game environment for research applications. The FireCommander is an interactive, probabilistic joint perception-action reconnaissance environment in which…

Robotics · Computer Science 2021-10-29 Esmaeil Seraj , Xiyang Wu , Matthew Gombolay

We introduce POGEMA (https://github.com/AIRI-Institute/pogema) a sandbox for challenging partially observable multi-agent pathfinding (PO-MAPF) problems . This is a grid-based environment that was specifically designed to be a flexible,…

Machine Learning · Computer Science 2022-06-23 Alexey Skrynnik , Anton Andreychuk , Konstantin Yakovlev , Aleksandr I. Panov

Progress in multiagent intelligence research is fundamentally limited by the number and quality of environments available for study. In recent years, simulated games have become a dominant research platform within reinforcement learning, in…

Machine Learning · Computer Science 2020-04-20 Joseph Suarez , Yilun Du , Igor Mordatch , Phillip Isola

We introduce a system called Amorphous Fortress -- an abstract, yet spatial, open-ended artificial life simulation. In this environment, the agents are represented as finite-state machines (FSMs) which allow for multi-agent interaction…

Artificial Intelligence · Computer Science 2023-06-26 M Charity , Dipika Rajesh , Sam Earle , Julian Togelius

Multiplayer Online Battle Arena (MOBA) is one of the most played game genres nowadays. With the increasing growth of this genre, it becomes necessary to develop effective intelligent agents to play alongside or against human players. In…

Artificial Intelligence · Computer Science 2017-06-12 Victor do Nascimento Silva , Luiz Chaimowicz

The emergence of complex life on Earth is often attributed to the arms race that ensued from a huge number of organisms all competing for finite resources. We present an artificial intelligence research environment, inspired by the human…

Multiagent Systems · Computer Science 2019-03-05 Joseph Suarez , Yilun Du , Phillip Isola , Igor Mordatch

Artificial Intelligence, when amalgamated with games makes the ideal structure for research and advancing the field. Multi-agent games have multiple controls for each agent which generates huge amounts of data while increasing search…

Artificial Intelligence · Computer Science 2021-11-30 Harsh Panwar , Saswata Chatterjee , Wil Dube

In multi-agent learning, agents must coordinate with each other in order to succeed. For humans, this coordination is typically accomplished through the use of language. In this work we perform a controlled study of human language use in a…

Computation and Language · Computer Science 2020-09-15 Takuma Yoneda , Matthew R. Walter , Jason Naradowsky

In this paper, we demonstrate the application of Fuzzy Markup Language (FML) to construct an FML-based Dynamic Assessment Agent (FDAA), and we present an FML-based Human-Machine Cooperative System (FHMCS) for the game of Go. The proposed…

Computer games are very challenging to handle for traditional automated testing algorithms. In this paper we will look at intelligent agents as a solution. Agents are suitable for testing games, since they are reactive and able to reason…

This work introduces Amorphous Fortress Online -- a web-based platform where users can design petri-dish-like environments and games consisting of multi-agent AI characters. Users can play, create, and share artificial life and game…

Artificial Intelligence · Computer Science 2025-02-11 M Charity , Mayu Wilson , Steven Lee , Dipika Rajesh , Sam Earle , Julian Togelius

While artificial intelligence has been applied to control players' decisions in board games for over half a century, little attention is given to games with no player competition. Pandemic is an exemplar collaborative board game where all…

Artificial Intelligence · Computer Science 2021-03-23 Konstantinos Sfikas , Antonios Liapis

Automated testing of computer games is a challenging problem, especially when lengthy scenarios have to be tested. Automating such a scenario boils down to finding the right sequence of interactions given an abstract description of the…

Software Engineering · Computer Science 2024-05-21 Samira Shirzadeh-hajimahmood , I. S. W. B. Prasteya , Mehdi Dastani , Frank Dignum

A simple model for cooperation between "selfish" agents, which play an extended version of the Prisoner's Dilemma(PD) game, in which they use arbitrary payoffs, is presented and studied. A continuous variable, representing the probability…

Condensed Matter · Physics 2009-11-10 H. Fort

We investigate an algorithm that assigns to any game in normal form an approximating game that admits an ordinal potential function. Due to the properties of potential games, the algorithm equips every game with a surrogate reward structure…

Multiagent Systems · Computer Science 2026-02-24 Philipp Lakheshar , Sharwin Rezagholi

The ability to learn optimal control policies in systems where action space is defined by sentences in natural language would allow many interesting real-world applications such as automatic optimisation of dialogue systems. Text-based…

Computation and Language · Computer Science 2018-01-09 Mikuláš Zelinka
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