Xavier Llorà » Human-Computer Interaction

GECCO 2010 Submission Deadline (Extended)

Xavier — Sat, 19 Dec 2009 12:11:34 +0000

If you are planning to submit a paper for the 2010 Genetic and Evolutionary Computation Conference, the deadline is January 13, 2010 (and now extended to January 27th). You can find more information at the GECCO 2010 calendar site. Related posts: GECCO 2009 paper submission deadline extended till January 28 GECCO 2011 Submission Deadline: January [...] Related posts:

Ben Shneiderman at UIUC

Xavier — Wed, 18 Apr 2007 17:03:44 +0000

You can find my notes for his presentation here.

One talk and a visit to UK

Xavier — Mon, 09 Oct 2006 01:06:03 +0000

September 21 I was invited to give a talk at the Computer Science Department at UIUC. During the talk “Combating User Fatigue and Contradictions in Subjective-based Optimization Schemes” I reviewed some of the research I have been involved about active interactive genetic algorithms. The PDF of the presentation can be downloaded here. I also gave the same presentation to some of the members of the ASAP research group at the University of Nottingham. Natalio Krasnogor invited me for a visit. The main topic was latest advances on Pittsburgh LCS (Jaume Bacardit is working there on protein folding problems using Pitt-style LCS). I really enjoyed interact with people there—lots of challenges and interesting discussions. Oh, I almost forgot, the three days I was in Nottingham I saw the sun most of the day .

Evolving emotional prosody

Xavier — Sun, 17 Sep 2006 15:57:30 +0000

by Cecilia Ovesdotter Alm and Xavier Llorà (2006).
Proceedings of the Ninth International Conference on Spoken Language Processing (INTERSPEECH 2006), paper 1741. Also as IlliGAL TR No 2006018. Link to the PDF.

Abstract
Emotion is expressed by prosodic cues, and this study uses the active interactive Genetic Algorithm to search a wide space for sad and angry parameters of intensity, F0, and duration in perceptual resynthesis experiments with users. This method avoids large recorded databases and is flexible for exploring prosodic emotion parameters. Solutions from multiple runs are analyzed graphically and statistically. Average results indicate parameter evolution by emotion, and appear best forsad speech. Solutions are quite successfully classified by CART, with duration as main predictor.

GECCO 2006

Xavier — Sat, 08 Jul 2006 18:14:50 +0000

Well, it finally happened. GECCO started today at 8:30am. You can find live blogging at the IlliGAL Blogging. Related posts: GECCO 2007 Hat Trick Yes, GECCO 2008 was intense! GECCO 2010 Submission Deadline (Extended) Related posts:

Analyzing active interactive genetic algorithms using visual analytics

Xavier — Fri, 07 Jul 2006 19:54:53 +0000

by Xavier Llorà, Kumara Sastry , Francesc Alías, David E. Goldberg, and Michael Welge (2006).
Proceedings of the ACM Genetic and Evolutionary Computation Conference (GECCO 2006), pp. 1417–1418, ACM press. Also as IlliGAL TR No 2006004. Link to the PDF.

Abstract
This paper build on active interactive genetic algorithms and introduces visual-analytic techniques to aggregate, summarize, and visualize the information generated during interactive evolutionary processes. Special visualizations of the user-provided partial ordering of solutions, the synthetic fitness surrogates induced, and the model of user preferences were prepared. The visual-analytic techniques proposed point out potential pitfalls, strengths, and possible improvements in a non-trivial case study where the hierarchical tournament selection scheme of an active interactive genetic algorithm is replaced by an equivalent incremental selection scheme. Visual analytics provided an intuitive reasoning environment that unveiled important properties that greatly affect the performance of active interactive genetic algorithms that could not have been easily reveled otherwise.

Innovation and creativity support via chance discovery, genetic algorithms, and data mining

Xavier — Wed, 01 Mar 2006 17:28:45 +0000

by Xavier Llorà and David E. Goldberg, Yukio Ohsawa, Naohiro Matsumura, Yuichi Washida, Hiroshi Tamura, Masataka Yoshikawa, Michael Welge, Loretta Auvil, Duane Searshmith, Kei Ohnishi, and Chen-Ju Chao (2006).
New Mathematics and Natural Computation, World Scientific, pp. 2(1):85–100. Link to the Journal publication.

Abstract
Creativity protocols and methodologies tend to be time consuming if applied manually. This paper presents how information technologies can support innovation and creativity for collaborative scenario creation and discussion. The fusion of change discovery, genetics algorithms, and computer-supported collaborative tools provide computational models of innovation and creativity. The proposed technology allows groups of participants in a creative processes to have pervasive access to the analysis of the current scenario in real time. This paper introduces such innovation technologies gathered in the DISCUS project, and summarizes initial successful usages of DISCUS on marketing research workshops.

The innovation pump: Supporting creative processes in collaborative engineering

Xavier — Sun, 26 Feb 2006 22:45:54 +0000

by Xavier Llorà and David E. Goldberg (2006).
IlliGAL TR No 2006011. Link to the PDF.

Abstract
The pervasive expansion of computers and Internet has change the way people collaborate. Terms such as cybercollaboratories are getting traction in day-to-day work. Web boards, blogs, e-mails, and instant messaging have become {\em de facto} mainstream communication channels. People scattered across the globe collaborate thanks to such technologies to carry out their daily work. Creative processes—such as collaborative engineering—have also taken advantage of such new communication media. This paper reviews the new framework set after these technologies and presents how collaborative creativity and innovation can be modeled and supported using computational models. The paper continues presenting a innovation-support model based on the usage of genetic algorithms as computational metaphors of human innovation. The paper also briefly discuses the results achieved using the proposed technologies in real-world collaborative creative processes.

A simple UMDAc implementation in Java

Xavier — Tue, 06 Dec 2005 06:04:55 +0000

Cecilia Oversdotter is working on an adaptation of active interactive genetic algorithms (some papers can be found here and here) to her work on speech synthesis and perception of emotions in expressive storytelling. She needs a version of the active interactive genetic algorithm that works on continuous domains. For that reason I coded a version of UMDAc to replace the cGA currently used for discrete domains.

The Java implementation of UMDAc can be found here. In order to run it, you need to download the COLT toolkit . The code is distributed under GPL license.

Evaluation consistency in iGAs: User contradictions as cycles in partial-ordering graphs

Xavier — Mon, 28 Nov 2005 01:06:23 +0000

by Francesc Alías, Xavier Llorà, Lluís Formiga, Kumara Sastry, and David E. Goldberg (2006, accepted).
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2006). May 14-19, 2006. Also as IlliGAL TR No 2005022. Link to the PDF.

Abstract
Active interactive genetic algorithms (aiGAs) rely on actively optimizing synthetic fitness functions. In interactive genetic algorithms (iGAs) framework, user evaluations provide the necessary input for synthesizing a reasonably accurate surrogate fitness function that models user evaluations or, in other words, his/her decision preferences. User evaluations collected via tournament selection only provide partial-ordering relations between solutions. Active iGAs assemble a partial-ordering graph of user evaluations. In such a directed graph, any contradictory evaluation provided by the user introduces a cycle in the graph. This property is explored in this paper to measure the consistency of the evaluations provided by the user along the evolutionary process. The consistency measures are applied to a real-world problem, the weight tuning of the cost function involved in corpus-based text-to-speech synthesis. Results show the usefulness of such measures to identify inconsistent users during the evolutionary tuning process, and successfully the number of evaluations required by more than half.