EvoMan: Game-playing Competition

This paper describes a competition proposal for evolving Intelligent Agents for the game-playing framework called EvoMan. The framework is based on the boss fights of the game called Mega Man II developed by Capcom. For this particular competition, the main goal is to beat all of the eight bosses using a generalist strategy. In other words, the competitors should train the agent to beat a set of the bosses and then the agent will be evaluated by its performance against all eight bosses. At the end of this paper, the competitors are provided with baseline results so that they can have an intuition on how good their results are.

READ FULL TEXT
research
09/11/2022

Keke AI Competition: Solving puzzle levels in a dynamically changing mechanic space

The Keke AI Competition introduces an artificial agent competition for t...
research
03/14/2018

The 2017 AIBIRDS Competition

This paper presents an overview of the sixth AIBIRDS competition, held a...
research
06/29/2019

Ludii as a Competition Platform

Ludii is a general game system being developed as part of the ERC-funded...
research
05/19/2022

A Novel Weighted Ensemble Learning Based Agent for the Werewolf Game

Werewolf is a popular party game throughout the world, and research on i...
research
07/07/2018

How game complexity affects the playing behavior of synthetic agents

Agent based simulation of social organizations, via the investigation of...
research
08/13/2019

Playing log(N)-Questions over Sentences

We propose a two-agent game wherein a questioner must be able to conjure...
research
03/26/2022

Competition-Based Resilience in Distributed Quadratic Optimization

This paper proposes a novel approach to resilient distributed optimizati...

Please sign up or login with your details

Forgot password? Click here to reset