Generating Levels That Teach Mechanics

The automatic generation of game tutorials is a challenging AI problem. While it is possible to generate annotations and instructions that explain to the player how the game is played, this paper focuses on generating a gameplay experience that introduces the player to a game mechanic. It evolves small levels for the Mario AI Framework that can only be beaten by an agent that knows how to perform specific actions in the game. It uses variations of a perfect A* agent that are limited in various ways, such as not being able to jump high or see enemies, to test how failing to do certain actions can stop the player from beating the level.Comment: 8 pages, 7 figures, PCG Workshop at FDG 2018, 9th International Workshop on Procedural Content Generation (PCG2018

AI Researchers, Video Games Are Your Friends!

If you are an artificial intelligence researcher, you should look to video games as ideal testbeds for the work you do. If you are a video game developer, you should look to AI for the technology that makes completely new types of games possible. This chapter lays out the case for both of these propositions. It asks the question "what can video games do for AI", and discusses how in particular general video game playing is the ideal testbed for artificial general intelligence research. It then asks the question "what can AI do for video games", and lays out a vision for what video games might look like if we had significantly more advanced AI at our disposal. The chapter is based on my keynote at IJCCI 2015, and is written in an attempt to be accessible to a broad audience.Comment: in Studies in Computational Intelligence Studies in Computational Intelligence, Volume 669 2017. Springe

Computación evolutiva aplicada al desarrollo de videojuegos: Mario AI

A lo largo de la historia el juego y los videojuegos han tenido una evolución paralela, actualmente han evolucionado considerablemente hasta convertirse en productos de alta tecnología. En el caso de los videojuegos se han convertido en una industria muy fuerte con un volumen de negocio comparable al cinematográfico. Hasta hace unos años, el desarrollo de los videojuegos se ha centrado en el apartado gráfico y el apartado sonoro, dejando a un segundo plano el comportamiento de los NPCs (Non Player Character). En la actualidad está habiendo una tendencia a centrarse cada vez más en la inteligencia artificial (IA) de los NPCs, que da lugar a numerosos avances e investigaciones relacionadas con la IA con el objetivo de proporcionar a los usuarios de videojuegos un comportamiento variable e impredecible de los NPC tanto en los enemigos como compañeros que se encuentra el usuario a lo largo del videojuego. El presente proyecto se centra en aplicar alguna de las técnicas de IA existentes a un videojuego, para ello se ha realizado un estudio con diferentes videojuegos en los cuales se pueden aplicar técnicas de IA, seguidamente se hará una elección justificada de uno de los videojuegos analizados. A continuación se determinarán que técnicas son susceptibles a aplicar al videojuego elegido, y se elegirá una de estas técnicas, en esta investigación se ha elegido la técnica de IA Algoritmos Genéticos (AG) dentro de la Computación Evolutiva, y Mario AI como el videojuego a probar. La novedad de esta investigación reside en que se desarrolla un agente autónomo e inteligente capaz de completar varios niveles del videojuego en cuestión, mediante la utilización de los AGs. El resultado obtenido tras la realización del proyecto ha sido exitoso. Se ha comprobado que los AGs son apropiados en la creación de agentes que son capaces de superar diferentes niveles de Mario AI con dificultad variable. Para comprobar finalmente la calidad de la solución se decide participar en la competición Mario AI Championship 2011, que se celebrará el próximos mes de noviembre, en GIC2011. Al compararse con los resultados de años anteriores se ha verificado que el agente desarrollado en el presente proyecto obtiene puntuaciones mayores que los participantes de la competición en años anteriores. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Throughout history the games and videogames have had parallel evolution, nowadays it have evolved considerably until it becomes high-tech products. Videogames has become a strong industry with a turnover comparable with movie industry. Until recently, the videogames development has focused on the graphics and sound sections, leaving the background the behavior of NPCs (Non Player Character). But now, there is a tendency to focus increasingly on the Artificial Intelligence (AI) of NPCs, so it makes many advances and researches related to AI in order to provide videogames users variables and unpredictable behaviors of enemies and partners NPCs throughout the videogame. This project focuses on applying some of the existing IA techniques to a videogame, it has made a study with different videogames which can apply these AI techniques, and afterward it has made a justified election of one of the analyzed videogames. Next, it has determined that IA techniques can be to apply to chosen videogame, and it has chosen one of these techniques, this research has chosen the Genetic Algorithms (GA) in Computation Evolutionary as the AI technique, and Mario AI as the videogame to try. The innovation of this research is to develop an intelligent and autonomous agent that is capable of completing various levels of the videogame in question through the use of GAs. The obtained results after of making the project have been successful. There is evidence that GAs are appropriate in the creation of agents that able to overcome different levels with varying difficulty of Mario AI. To check finally the quality of the solution it has decided to take part in the "Mario AI Championship 2010" competition, to be held the next November in GIC2011. When it has compared with the previous years results, it has verified that the developed agent, in this project, gets higher scores that the participants of the competition in previous years.Ingeniería en Informátic

15th Annual Las Vegas Holiday Classic

Team rosters for all schools. UNLV Schedule UNLV Varsity Schedule List of UNLV Scholarship Donors Meet the Rebels Opponent\u27s Scouting Report Registration for the 1976 Jerry Tarkanian Basketball Camps Jerry Tarkanian Stor