Paper Info
Title
Specifying complex systems with bayesian programming. an alife application
Abstract
One of the most important application areas of Artificial Life is the simulation of complex processes. This paper shows how to use Bayesian Programming to model and simulate an artificial life problem: that of a worm trying to live in a world full of poison. Any model of a real phenomenon is incomplete because there will always exist unknown, hidden variables that influence the phenomenon. To solve this problem we apply a new formalism, Bayesian programming. The proposed worm model has been used to train a population of worms using genetic algorithms. We will see the advantages of our method compared with a classical approach. Finally, we discuss the emergent behaviour patterns we observed in some of the worms and conclude by explaining the advantages of the applied method. It is this characteristic (the emergent behaviour) which makes Artificial Life particularly appropriate for the study and simulation of complex systems for which detailed analysis, using traditional methods, is practically non-viable.
Year
DOI
Venue
2005
10.1007/11428831_103
International Conference on Computational Science (1)
Keywords
Field
DocType
artificial life problem,bayesian programming,real phenomenon,emergent behaviour pattern,complex system,emergent behaviour,alife application,applied method,complex process,proposed worm model,artificial life
Complex system,Computer science,Bayesian programming,Artificial intelligence,Distributed computing
Conference
Volume
ISSN
ISBN
3514
0302-9743
3-540-26032-3
Citations 
PageRank 
References 
0
0.34
5
Authors
3
Name
Order
Citations
PageRank
fidel aznar gregori173.19
Mar Pujol López2288.54
R. Rizo35114.90