DREAM

01/03/2000 - 31/05/2003

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This project seeks to provide the technology and software infrastructure necessary to support the next generation of evolving infohabitants in a way that makes that infrastructure universal, open and scalable. The Distributed Resource Evolutionary Algorithm Machine (DREAM) will use existing hardware infrastructure in a much more efficient manner, by utilising otherwise unused CPU time. It will allow infohabitants to co-operate, communicate, negotiate and trade; and emergent behaviour is expected to result. It is expected that there will be an emergent economy that results from the provision and use of CPU cycles by infohabitants and their owners. The DREAM infrastructure will be evaluated with new work on distributed data mining, distributed scheduling and the modelling of economic and social behaviour.
DREAM is a EU Framework Programmes project funded by European Commission. Carried out in collaboration with and others. For further information please refer to http://www.world-wide-dream.org.
 
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Project Team

Ben Paechter
Director of Research
b.paechter@napier.ac.uk
+44 131 455 2764

Associated Publications

Lewis, R., Paechter, B. (2007). Finding Feasible Timetables Using Group-Based Operators. IEEE Transactions on Evolutionary Computation, 11, (3), 397-413.

Lewis, R., Paechter, B., Rossi-Doria, O. (2006). Metaheuristics for University Course Timetabling. In: Cowling, P., Dahal, K. (Eds.) Evolutionary Scheduling, , () ( ed.). (pp. ). : . Springer-Verlag.

Craenen, B., Paechter, B. (2005). Peer-to-peer networks for scalable grid landscapes in social agent simulations. In: (Ed.) Proceedings of the Artificial Intelligence and Social Behaviour Convention (AISB) 2005, , () ( ed.). (pp. ). Hatfield: . .

Lewis, R., Paechter, B. (2005). An Emprical Analysis of the Grouping Genetic Algorithm: the Timetabling Case. In: (Ed.) The 2005 IEEE Congress on Evolutionary Computation, , () ( ed.). (pp. 2856-2863). Edinburgh, Scotland: . IEEE Computer Society Press.

Lewis, R., Paechter, B. (2005). Application of the Grouping Genetic Algorithm to University Course Timetabling. In: Gottlieb, ., Raidl, . (Eds.) 5th European Conference in Evolutionary Computation in Combinatorial Optimisation (EvoCop 2005), LNCS 3448, () (LNCS 3448 ed.). (pp. 144-153). Lausanne, Swizerland: . Springer-Verlag.

de Toro Negro, F., Ortega, J., Ros, E., Mota, S., Paechter, B., Martin, J.M. (2004). PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation. Parallel Computing, 30, (5-6), 551-816.

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