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The International Symposium on Distributed Computing and Artificial Intelligence 2012 (DCAI 2012) is a stimulating and productive forum where the scientific community can work towards future cooperation in Distributed Computing and Artificial Intelligence areas. This conference is a forum in which applications of innovative techniques for solving complex problems will be presented. Artificial intelligence is changing our society. Its application in distributed environments, such as the internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to mention only a few, is continuously increasing, becoming an element of high added value with social and economic potential, in industry, quality of life, and research. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. The exchange of ideas between scientists and technicians from both the academic and industry sector is essential to facilitate the development of systems that can meet the ever increasing demands of today´s society.
This edition of DCAI brings together past experience, current work, and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This symposium is organized by the Bioinformatics, Intelligent System and Educational Technology Research Group of the University of Salamanca. The present edition will be held in Salamanca, Spain, from 28th to 30th March 2012.

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From the content: Mixed Odor Classification for QCM Sensor Data by Neural Networks.- A Predictive Search Method of FAQ Corresponding to a User´s Incomplete Inquiry by Statistical Model of ImportantWords Co-occurrence.- Decision making for sustainable manufacturing utilizing a manufacturing technology database.- Solving Time-Dependent Traveling Salesman Problems using Ant Colony Optimization Based on Predicted Traffic.- Modeling shared-memory metaheuristic schemes for electricity consumption.

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