“The L-Co-R co-evolutionary algorithm: a comparative analysis in medium-term time-series forecasting problems” at ECTA

Our paper “The L-Co-R co-evolutionary algorithm: a comparative analysis in medium-term time-series forecasting problems” was accepted for oral presentation in the latest ECTA-IJCCI conference.

The abstract:
This paper presents an experimental study in which the effectiveness of the L-Co-R method is tested. L-Co-R is a co-evolutionary algorithm to time series forecasting that evolves, on one hand, RBFNs building an appropriate architecture of net, and on the other hand, sets of time lags that represents the time series in order to perform the forecasting using, at the same time, its own forecasted values. This coevolutive approach makes possible to divide the main problem into two subproblems where every individual of one population cooperates with the individuals of the other. The goal of this work is to analyze the results obtained by L-Co-R comparing with other methods from the time series forecasting field. For that, 20 time series and 5 different methods found in the literature have been selected, and 3 distinct quality measures have been used to show the results. Finally, a statistical study confirms the good results of L-Co-R in most cases.


Paper “Testing the Differences of Using RGB and HSV Histograms During Evolution in Evolutionary Art” in ECTA

This week we are presenting the paper “Testing the Differences of Using RGB and HSV Histograms During Evolution in Evolutionary Art” in the Evolutionary Computation Theory and Applications.

This is the work we developed in the Hackathon of the Spanish Free Software Contest of the University of Granada with the help of several students of our university (who are also authors!).

In this work we have added Processing to our OSGiLiath (service oriented architecture for evolutionary algorithms) framework to generate images from individual representations to work with generative art. The fitness is the equality to a predefined image. HSV, RGB and a combination of both have been used.

The abstract:

This paper compares the use of RGB and HSV histograms during the execution of an Evolutionary Algorithm. This algorithm generates abstract images that try to match the histograms of a target image. Three different fitness functions have been used to compare: the differences between the individual with the RGB histogram of the test image, the HSV histogram, and an average of the two histograms at the same time. Results show that the HSV fitness also increases the similarities of the RGB (and therefore, the average) more than the other two measures.

And here is the poster:


OSGiLiath at #GECCO2013

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OSGiLiath Evolutionary Framework

This week several members of Geneura group and ANYSELF project are attending to GECCO 2013 conference in Amsterdam. I’ve presented two papers related with OSGiLiath:

The first one, entitled Developing Services in a Service Oriented Architecture for Evolutionary Algorithms has been presented inside the EvoSoft workshop. It is a more technical continuation of the work “Service Oriented Evolutionary Algorithms“. Here is the abstract:

This paper shows the design and implementation of services for Evolutionary Computation in the Service Oriented Architecture paradigm. This paradigm allows independence in language and distribution, but the development requires to manage some technological and design issues, such as abstract design or unordered execution. To solve them, OSGiLiath, an implementation of an abstract Service Oriented Architecture for Evolutionary Algorithms, is used to develop new interoperable services taking into account these restrictions.

And here the presentation:

I also have presented the work “A Service Oriented…

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Unreal Expert Bots at IWANN 2013

Last week there was held IWANN 2013 at Tenerife, an international conference mainly devoted to researches inside the neural networks scope. In it, Antonio Fernández Leiva, Raúl Lara and Me organized the Special Session on Artificial Intelligence and Games.

There were five works in the session, one of them “Designing and Evolving an Unreal Tournament— 2004 Expert Bot“.

It describes the designing and improvement, through off-line (not during the game) evolution, of an autonomous agent (or bot) for playing the game Unreal Tournament 2004. This was created by means of a finite state machine which models the expert behaviour of a human player in 1 vs 1 deathmatch mode, following the rules of the international competition.

Then, the bot was improved by means of a Genetic Algorithm, yielding an agent that is, in turn a very hard opponent for the medium-level human player and which can (easily) beat the default bots in the game, even in the maximum difficulty level.

The presentation can be seen at:

Moreover, you can watch one example of the evolution in the following video:

Finally, the Unreal Expert and Genetic bot’s source code are available at https://github.com/franaisa/ExpertAgent

Enjoy them. ;)

More results of the hispano-mexican collaboration

As a result of a collaboration with Mario García Valdez, Leonardo Trujillo and Francisco Fernández (this one from Spain) we have published two papers based on the EvoSpace framework a pool-based evolutionary architecture for interactive and straight evolutionary computation. The first paper describes the EvoSpace-i, the interactive part and is well described by Paco Fernández in our group blog, and the

Super Mario autonomous agents at LION 2013

Recently, inside the last LION 7 (2013) conference (Special Session on Games and Computational Intelligence) there was presented the paper entitled “FSM-Based Agents for Playing Super Mario Game”.

It describes the implementation and test of an autonomous agent which can play Super Mario game better than an expert user can do (in some trained levels).
It is build starting from a Finite State Machine and applying an Evolutionary Algorithm.

The presentation is:

You can watch one example of the obtained agent playing a game here:

Enjoy it. ;)

Service Oriented Evolutionary Algorithms paper accepted

I am happy to announce that my paper Service Oriented Evolutionary Algorithms has been accepted in the Soft Computing Journal (Impact Factor 1.88). This paper describes some ideas about how the Evolutionary Algorithms should be defined in the Service Oriented Architecture paradigm. OSGiLiath is also described as a technological example (and the specific usage of OSGi and ECF).

The abstract:

This work presents a Service Oriented Architecture for Evolutionary Algorithms (SOA-EA), and an implementation of this architecture using a specific technology (called OSGiLiath). Service Oriented Architecture is a computational paradigm where users interact using services to increase the integration between systems. The presented abstract architecture is formed by loosely coupled, highly configurable and language-independent services. As an example of an implementation of this architecture, a complete process development using a specific service oriented technology is explained. With this implementation, less effort than classical development in integration, distribution mechanisms and execution time management has been attained.
In addition, steps, ideas, advantages and disadvantages, and guidelines to create service oriented evolutionary algorithms are presented. Using existing software, or from scratch, researchers can create services to increase the interoperability in this area.

I’ll update the final reference after the final publication, but if you are interested in receive a draft version, just let me know.

More information about the OSGiLiath project is available in the official page.