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!

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Is entropy good for solving the game of MasterMind?

Well, it does. In another paper published in the Evostar conference, we compare several methods for measuring how good a combination is when compared to the others that could possibly be the solution; so far we had mostly used most parts (counting the number of non-zero partitions), but, in this paper, that compares our previous Evo method with another created by the coauthors, Maestro-Montojo and Salcedo-Sanz, we find that Entropy, at least for these sizes, is the way to go. Here’s the poster


You can access the paper Comparing Evolutionary Algorithms to Solve the Game of MasterMind, by Javier Maestro-Montojo, Juan Julián Merelo and Sancho Salcedo-Sanz (first and last authors from the University of Alcalá de Henares) online or request a copy from the authors.

Going a bit farther (and a bit faster) solving MasterMind using evolutionary algorithms

We left MasterMind last year in a good state using estimation of distribution algorithms; however, if we want to find a solution for higher dimensions (more colors, more pegs) we have to improve the number of evaluations. In this case we use something we call endgames; same as chess playing algorithms use a database of endgames for ending a game in a straightforward way, in MasterMind we can recognize a few occasions in which the search space is reduced drastically and it’s better either change the strategy or just change the search space. When we know the colors (that is, we obtain as many white+blacks as the length of the combination) the best is to just revert to exhaustive search over combination space; when the answer is 0 whites/blacks we can also exclude those colors from the search space and start, maybe with a smaller population.
This is what we do in the paper Improving and Scaling Evolutionary Approaches to the MasterMind Problem , which was presented a short time ago in the EvoGames workshop in Torino
IMG_1235
During the presentation, Carlos Cotta and Carlos Fernandes played the game shown above.
Here’s the presentation, which you can download at ease. Picture credits are included in the notes.