Xavier Llorà » Journals

Communication gap management for fertile community

Xavier — Sat, 24 Mar 2007 15:17:35 +0000

by Naohiro Matsumura, David E. Goldberg, and Xavier Llorà (2006).
Journal of Soft Computing, Volume 11 , Issue 8, pp. 791–798, ACM press. Link to the ACM portal.
Initial work also available as IlliGAL TR No 2005001. Link to the PDF.

Abstract
In the paper, we first present an approach to extract social networks from message boards on the Internet. Then we propose communication gaps based on structural features of the social networks as an indicator of understanding the state of communication. After we classify 3,000 social networks into three types of communication, i.e., interactive communication, distributed communication, and soapbox communication, we suggest communication gap management to identify the types of communication, the roles of individuals, and important ties, all of which can be used for drawing up a plan for realizing fertile community.

Toward routine billion-variable optimization using genetic algorithms

Xavier — Thu, 18 Jan 2007 22:32:36 +0000

by Goldberg, D. E., Sastry, K., and Llorà X. (2007).
Complexity, 12(3), 27—29. Link to the PDF. Press release.

The push for better understanding and design of complex systems requires the solution of challenging optimization problems with large numbers of decision variables. This note presents principled results demonstrating the scalable solution of a difficult test function on instances over a billion variables using a parallel implementation of a genetic algorithm (GA). The problem addressed is a noisy, blind problem over a vector of binary decision variables. Noise is added equaling a tenth of the deterministic objective function variance of the problem, thereby making it difficult for simple hillclimbers to find the optimal solution. The genetic algorithm used – the compact GA – is able to find the optimum in the presence of noise quickly, reliably, and accurately, and the solution scalability follows known convergence theories. These results on noisy problem together with other results on problems involving varying modularity, hierarchy, and overlap foreshadow routine solution of billion-variable problems across the landscape of complexity science.

E2K: Evolution to knowledge

Xavier — Wed, 13 Sep 2006 20:14:15 +0000

by Xavier Llorà (2006).
ACM SIGEvolution, Volume 1 , Issue 3, pp. 10-17. Link to the Journal.
Also as IlliGAL TR No 2006022. Link to the PDF.

Abstract
Evolution to Knowledge (E2K) is a set of Data to Knowledge (D2K) modules and itineraries that perform genetic algorithms (GA) and genetics-based machine learning (GBML) related tasks. The goal of E2K is to fold: simplify the process of building GA/GBML related tasks, and provide a simple exploratory workbench for the evolutionary computation community to help users to interact with evolutionary processes. It can help to create complex tasks or help the newcomer to get familiarized and trained with the evolutionary methods and techniques provided. Moreover, due to its integration into D2K, the creation of combined data mining and evolutionary task can be effortlessly done via the visual programming paradigm provided by the workflow environment and also wrap other evolutionary computation software.

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.