Our TORCS driving controller presented at EvoGAMES 2017

Last week, @jjmerelo presented at EvoGAMES 2017 (inside Evo* 2017) our work titled “Driving in TORCS using modular fuzzy controllers”.

This paper presents a novel car racing controller for TORCS (The Open Racing Car Simulator), which is based in the combination of two fuzzy subcontrollers, one for setting the speed, and one to control the steer angle. The obtained results are quite promissing, as the controller is quite competitive even against very tough TORCS teams.

The abstract of the paper is:

When driving a car it is essential to take into account all possible factors; even more so when, like in the TORCS simulated race game, the objective is not only to avoid collisions, but also to win the race within a limited budget. In this paper, we present the design of an autonomous driver for racing car in a simulated race. Unlike previous controllers, that only used fuzzy logic approaches for either acceleration or steering, the proposed driver uses simultaneously two fuzzy controllers for steering and computing the target speed of the car at every moment of the race. They use the track border sensors as inputs and besides, for enhanced safety, it has also taken into account the relative position of the other competitors. The proposed fuzzy driver is evaluated in practise and timed races giving good results across a wide variety of racing tracks, mainly those that have many turning points.

There was an interactive presentation at the conference, together with a poster:

The paper is available online from: https://link.springer.com/chapter/10.1007/978-3-319-55849-3_24

Enjoy (and cite) it! :D

 

EvoGAMES is coming… Check out the CFP

The deadline for submitting your paper to EvoGAMES (and the rest of Evo*) is now set (1 November).

EvoGAMES is a track of the European Conference on the Applications of Evolutionary Computation focused on the applications of bio-inspired algorithms in games.

The areas of interest for the track include, among others:
Computational Intelligence in video games
  – Intelligent avatars and new forms of player interaction
  – Player experience measurement and optimization
  – Procedural content generation
  – Human-like artificial adversaries and emotion modelling
  – Authentic movement, believable multi-agent control
  – Experimental methods for gameplay evaluation
  – Evolutionary testing and debugging of games
  – Adaptive and interactive narrative and cinematography
  – Games related to social, economic, and financial simulations
  – Adaptive educational, serious and/or social games
  – General game intelligence (e.g. general purpose drop-n-play Non-Player Characters, NPCs)
  – Monte-Carlo tree search (MCTS)
  – Affective computing in Games

Important dates are:
– Submission of papers: 1 November 2015
– Notification: 4 January 2015
– Camera-ready: 18 January 2015
– Evo* dates: 30 March – 1 April 2016

This year, the page limit has been increased up to 16 pages, so you could write more and more scientific content. :D

As usual, the accepted submissions will be included in the proceedings of Evo*, published in a volume of the Springer Lecture Notes in Computer Science.

For more info about the conference and the track you can visit the Main site of Evo* 2016.

See you in Porto!

Ms. PacMan in IEEE Transactions on CI and AI in Games

Our fans and followers must be happy! ;D

They can now access the excellent work by Federico Liberatore in IEEE ToCIAIG journal.

This is the best journal concerning Artificial Intelligence in games, with a very strict reviewing process, so, we are very proud of this success. ;)

This is the next step in the research started one year and a half ago designing competitive  Ghost Teams for catching Ms. PacMan.

The abstract is:

In the last year, thanks to the Ms. Pac-Man vs Ghosts competition, the game of Ms. Pac-Man has gained increasing attention from academics in the field of Computational Intelligence. In this work, we contribute to this research stream by presenting a simple Genetic Algorithm with Lexicographic Ranking (GALR) for the optimization of Flocking Strategy-based ghost controllers. Flocking Strategies are a paradigm for intelligent agents characterized by showing emergent behavior and for having very little computational and memory requirements, making them well suited for commercial applications and mobile devices. In particular, we study empirically the effect of optimizing homogeneous and heterogeneous teams. The computational analysis shows that the Flocking Strategy-based controllers generated by the proposed GALR outperform the ghost controllers included in the competition framework and some of those presented in the literature.

The paper can be found here: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7093170&tag=1

Enjoy it!

(And cite us) :D

How I stayed in Granada for 15 days and failed to visit the Alhambra

Let me introduce myself: I am Alberto Tonda, a computer scientist originally from Italy, now working in a French national research center. In the picture below, there’s me looking extremely professional, with a lightsaber. I was at a wedding. Wedding with lightsabers are the best!In 2014, the University of Granada (UGR) hosted the international conference EvoSTAR: me and my co-authors won the Best Paper award, and as a prize we received funding to work with a research team at UGR.

I then contacted the GeNeura team to start a cooperation, and a few months later I was in Granada. I was extremely impressed with how welcoming the GeNeura guys were! They took care of all the administrative business (and, as researchers, we know how much this can be annoying :-D), they showed me around the city, they fed me delicious tapas, and they were an all-around pleasant people.

Here is me again, presenting my work to the team (by the way, here is a link to the presentation). It took us a while to find a common topic to work on, with lots of stimulating brainstorming, and evenalberto-geneuratually we started an exciting work on machine learning. I worked more in direct contact with Pablo Garcia and Antonio “Antares” Ares, but all people from GeNeura pitched in their ideas and were extremely helpful: J. J. Merelo, Antonio Mora, Pedro Castillo, and all the others I am forgetting (sorry, I am terrible with names!).

So, my only regret is that I didn’t visit the renown Alhambra, the beautiful fortress-palace Granada is famous for.Looks awesome. I had even bought a ticket (!) and was preparing for a late afternoon visit after work, when something every computer scientist dreads happened: the program I wrote with Pablo was almost working. So, since that was our last working day before I left, and our task was so engaging, I decided to stay and make it work. And by evening, we made it work, so at least giving up the visit was worth something!

In conclusion, I’d definitely recommend cooperating with GeNeura. And since our work together is far from finished, I have a good excuse to come back and finally visit the Alhambra :-)

Aplicación de Programación Genética para la generación de bots del RTS Planet Wars en CoSECiVi 2014

Este trabajo se publicó dentro del Primer Congreso de la Sociedad Española para las Ciencias del Videojuego (CoSECIVI), que se celebró en conjunción con el Gamelab 2014 en Barcelona.

En él se presentó el artículo titulado “Designing Competitive Bots for a Real Time Strategy Game using Genetic Programming”, cuyo resumen (en inglés) es:

The design of the Artificial Intelligence (AI) engine for an autonomous agent (bot) in a game is always a difficult task mainly done by an expert human player, who has to transform his/her knowledge into a behavioural engine. This paper presents an approach for conducting this task by means of Genetic Programming (GP) application. This algorithm is applied to design decision trees to be used as bot’s AI in 1 vs 1 battles inside the RTS game Planet Wars. Using this method it is possible to create rule-based systems defining decisions and actions, in an automatic way, completely different from a human designer doing them from scratch. These rules will be optimised along the algorithm run, considering the bot’s performance during evaluation matches. As GP can generate and evolve behavioural rules not taken into account by an expert, the obtained bots could perform better than human-defined ones. Due to the difficulties when applying Computational Intelligence techniques in the videogames scope, such as noise factor in the evaluation functions, three different fitness approaches have been implemented and tested in this work. Two of them try to minimize this factor by considering additional dynamic information about the evaluation matches, rather than just the final result (the winner), as the other function does.
In order to prove them, the best obtained agents have been compared with a previous bot, created by an expert player (from scratch) and then
optimised by means of Genetic Algorithms. The experiments show that the three used fitness functions generate bots that outperform the optimized human-defined one, being the area-based fitness function the one that produces better results.

La presentación del artículo se puede ver aquí:

El artículo se puede encontrar en: http://gaia.fdi.ucm.es/sites/cosecivi14/es/papers/24.pdf

Esperamos que os guste.

Y que nos citéis. :D

Hackathon in Videogames at EVO* 2014

Imagen

Hi to all,

Finally, the EVOHackathon will be held in the Oficina de Software Libre on Tuesday 22 April (one day before EVOGames conference).

There are 5 projects confirmed right now,namely:

  • Creating autonomous agents for Super Mario Bros. game
  • Creating an AI engine for the game Wetland (Greyman Studios)
  • Creating bots for 1 vs 1 combats in the RTS Planet Wars
  • Procedural generation of stages for a new game (Greyman Studios)
  • Progamer: Code visualization tool based in Super Mario Bros. levels

As you can see, two of them are proposed and will be directed by a videogames company.

We invite you to join us. It is free! :D

Modelando el conocimiento de un experto en Unreal Tournament (CEDI 2013)

En concreto, hemos presentado el artículo “Modelling Human Expert Behaviour in an Unreal Tournament 2004 Bot” dentro del Primer Simposio Español en Entretenimiento Digital, incluido dentro del CEDI 2013.

Y vosotros diréis, ¿por qué un artículo en inglés en un congreso español?. Pues porque los artículos en inglés que sean seleccionados podrán enviarse a un número especial de la revista Entertainment Computing (Elsevier). A ver si hay suerte. :D

El trabajo presenta el diseño de un bot (jugador autónomo) para jugar a Unreal Tournament 2004 (UT2K4). Dicho bot ha sido creado por Francisco Aisa y Ricardo Caballero, modelando el conocimiento y comportamiento de un jugador experto en dicho juego (el primero de ellos ;D).

La presentación podéis verla en:

Que la disfrutéis (y nos citéis, claro). :D

Saludos.