Ghost direction detection and other innovations for Ms. Pac-Man

Ms. Pac-Man was developed in the 1980s, becoming one of the most popular arcade games of its time. It still has a significant following today and has recently attracted the attention of artificial intelligence researchers, in part, due to the fact that the agent must react in real time in order to navigate its way through the maze. This pape

Ms Pac-Man versus Ghost Team CEC 2011 competition

Games provide an ideal test bed for computational intelligence and significant progress has been made in recent years, most notably in games such as Go, where the level of play is now competitive with expert human play on smaller boards. Recently, a significantly more complex class of games has received increasing attention: real-time video games. These games pose many new challenges, including strict time constraints, simultaneous moves and open-endedness. Unlike in traditional board games, computational play is generally unable to compete with human players. One driving force in improving the overall performance of artificial intelligence players are game competitions where practitioners may evaluate and compare their methods against those submitted by others and possibly human players as well. In this paper we introduce a new competition based on the popular arcade video game Ms Pac-Man: Ms Pac-Man versus Ghost Team. The competition, to be held at the Congress on Evolutionary Computation 2011 for the first time, allows participants to develop controllers for either the Ms Pac-Man agent or for the Ghost Team and unlike previous Ms Pac-Man competitions that relied on screen capture, the players now interface directly with the game engine. In this paper we introduce the competition, including a review of previous work as well as a discussion of several aspects regarding the setting up of the game competition itself. © 2011 IEEE

Monte-Carlo Tree Search Algorithm in Pac-Man Identification of commonalities in 2D video games for realisation in AI (Artificial Intelligence)

The research is dedicated to the game strategy, which uses the Monte-Carlo Tree Search algorithm for the Pac-Man agent. Two main strategies were heavily researched for Pac-Man’s behaviour (Next Level priority) and HS (Highest Score priority). The Pacman game best known as STPacman is a 2D maze game that will allow users to play the game using artificial intelligence and smart features such as, Panic buttons (where players can activate on or off when they want and when they do activate it Pacman will be controlled via Artificial intelligence). A Variety of experiments were provided to compare the results to determine the efficiency of every strategy. A lot of intensive research was also put into place to find a variety of 2D games (Chess, Checkers, Go, etc.) which have similar functionalities to the game of Pac-Man. The main idea behind the research was to see how effective 2D games will be if they were to be implemented in the program (Classes/Methods) and how well would the artificial intelligence used in the development of STPacman behave/perform in a variety of different 2D games. A lot of time was also dedicated to researching an ‘AI’ engine that will be able to develop any 2D game based on the users submitted requirements with the use of a spreadsheet functionality (chapter 3, topic 3.3.1 shows an example of the spreadsheet feature) which will contain near enough everything to do with 2D games such as the parameters (The API/Classes/Methods/Text descriptions and more). The spreadsheet feature will act as a tool that will scan/examine all of the users submitted requirements and will give a rough estimation(time) on how long it will take for the chosen 2D game to be developed. It will have a lot of smart functionality and if the game is not unique like chess/checkers it will automatically recognize it and alert the user of it

Uma arquitetura de subsunção com capacidades adaptativas preditivas para o Pacman

Dissertação de mest., Engenharia Informática, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2012Os jogos de computador são um domínio de estudo muito importante na área da inteligência computacional. Essa importância advém das propriedades de seus ambientes: multi-agente, competitivos, estocásticos e dinâmicos; onde a verificação de sucesso ou fracasso é de fácil verificação. Para além disso, os jogos e o entretenimento digital em geral, são uma industria em expansão que gera um volume de negócios considerável. O objetivo deste trabalho é desenvolver um agente para controlar o famoso pacman, capaz de participar numa das mais populares competições, organizadas pela conferência IEEE em inteligência computacional e jogos. Ganha a competição quem conseguir a pontuação média mais elevada de 3 execuções por equipa de fantasmas. O objetivo das equipas de fantasmas é fazer diminuir essas pontuações A dificuldade do pacman deve-se ao facto de fornecer um ambiente estocástico, dinâmico, parcialmente observável, ser um jogo do tipo predador/presa com 4 predadores e ocorrer dentro de um labirinto, o que condiciona os movimentos. A abordagem proposta neste trabalho é estender a arquitetura reativa de Brooks, a chamada arquitetura de subsunção com capacidades adaptativas e preditivas. O agente assim construído deverá ser capaz de prever o movimento dos fantasmas ao longo de um horizonte temporal no futuro, baseando-se num modelo que é atualizado com informação recolhida no passado e usar essas previsões para decidir o que fazer a seguir