Human-Computer Interaction

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 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. ...

Cecilia Oversdotter Alm is working on an adaptation of active interactive genetic algorithms (see 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. ...

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. ...

by Llorà, X., Sastry, K., Goldberg, D.E., Gupta, A., Lakshmi, L. (2005). Published in the ACM Genetic and Evolutionary Computation Conference (GECCO 2005), ACM press, pp. 1363–1371. Also as IlliGAL TR No 2005009. Link to the PDF Abstract: One of the daunting challenges of interactive genetic algorithms (iGAs)—genetic algorithms in which fitness measure of a solution is provided by a human rather than by a fitness function, model, or computation—is user fatigue which leads to sub-optimal solutions. This paper proposes a method to combat user fatigue by augmenting user evaluations with a synthetic fitness function. The proposed method combines partial ordering concepts, notion of non-domination from multiobjective optimization, and support vector machines to synthesize a fitness model based on user evaluation. The proposed method is used in an iGA on a simple test problem and the results demonstrate that the method actively combats user fatigue by requiring 3–7 times less user evaluation when compared to a simple iGA. ...