Philipp Rohlfshagen Title: Molecular Algorithms for Evolutionary Computation Abstract: Genetic algorithms are loosely based upon the field of population genetics. Their simplified implementation, detached from the intricate details of biological systems, is very efficient but bypasses a significant proportion of nature's ability to process and manipulate information. The significance of this omission has been exposed by recent advances in molecular genetics that have led to the assumption that the cellular information processing architecture is fundamental to the evolution of complex organisms. The objective of this talk is to review some of the recent advances in molecular genetics and to examine the contribution of cellular processes to the design of novel evolutionary algorithms. Major emphasis is placed upon the structure of eukaryotic genes and post-transcriptional processes. In particular, the central theme of this talk is the transition of genetic algorithms from the molecular level of prokaryotes to that of multi-cellular eukaryotes. We call this approach molecular algorithms. This talk will cover some aspects of our experimental work from the past 2 years. We will present a series of combinatorial optimisation algorithms, both problem dependent and problem independent. The biological principles exploited include the theory of exon shuffling, RNA editing, alternative splicing and properties of the genetic code. The algorithms are evaluated systematically on a number of artificially created problems, both static and dynamic, as well as a representative range of difficult combinatorial optimisation problems. Biography: Philipp Rohlfshagen recently submitted his PhD thesis after three years of study at the School of Computer Science, University of Birmingham, UK. Prior to the commencement of his PhD, Philipp received a MSc in Natural Computation from his current university (2004) and a BSc in Computer Science and Artificial Intelligence from the University of Sussex, UK (2003). He is a member of IEEE and the IEEE Computational Intelligence Society. His current research interests are the study and abstraction of cellular processes that may be used to enhance the computational power of classical evolutionary algorithms. Keywords: evolutionary computation, genetic algorithms, molecular genetics, combinatorial optimisation, dynamic optimisation Contact: P.Rohlfshagen@cs.bham.ac.uk and http://www.cs.bham.ac.uk/~pzr