Departamento de Ingeniería del Software e Inteligencia Artificial
Facultad de Informática
Universidad Complutense de Madrid
Title: How creative can reuse be?
Case-based reasoning has historically been a favoured technology for trying to model creative tasks such as story generation or music generation in AI. The overall idea that successful solutions to problems solved in the past may be used for problems in the present is intuitively valid for creative tasks. However, in contexts where a measure of creativity is expected, direct reuse of past solutions is not desirable. Traditional views of creativity require that some degree of novelty be exhibited by the solutions. From the point of view of case-based reasoning, this implies that significant levels of adaptation be applied or even that similarity be addressed in special ways to ensure exact matches are not considered. The talk will review a number of past efforts in the field of computational creativity to explore how this challenge has been addressed in terms of procedures for reusing past examples (usually known as the inspiring set) in such ways that valuable and novel instances of the desired artefacts are obtained.
Dr. Pablo Gervás of Universidad Complutense de Madrid is director of both the university's NIL research group (nil.fdi.ucm.es) and the Instituto de Tecnología del Conocimiento (www.itc.ucm.es). He is one of the world's leading experts on automatic generation of (fictional) stories and poetry, and has an extensive background in natural language generation, computational creativity and in narratology. His central research focus concerns the study of creativity as applied to the automated generation of literary artifacts with novelty, value and meaning for a human audience. His work on automated story generation has most recently contributed to the computer-assisted generation of a West-End musical in Britain titled "Beyond the Fence."
Vice President, Business Data Science
San Francisco, USA
Title: The Business End of Data Science
Born in Istanbul, Turkey. Lived a third of my life in Germany, one third in Turkey and one third in the US. Have a M.Sc. in Computer Science, an M.Sc. in Aerospace Engineering and a Ph.D. in Mechanical Engineering. I published my first paper on Expert Systems in 1989. After finishing my Ph.D. in Germany, I started my career at DaimlerBenz in Stuttgart. From there was transferred to their Palo Alto Research Lab - and have been in the Valley ever since. I have run the professional services for Kaidara in the US, led a research group at PriceWaterhouseCoopers and have been at Salesforce for the last 6 years. In my current role (VP of Business Data Science), my team and I analyze Customer Usage Data to determine adoption challenges, attrition risk and up-sell/cross-sell opportunities. Most of my research and work relates to using data to support decision making processes in an intuitive and personalized manner.