Dr Carron Shankland – University of Stirling
Direct evolution of process algebra model parameters
Process algebras are an effective method for defining models of complex interacting systems, especially biological systems, but tuning parameters to allow model outputs to match experimental data can be difficult. This is the well-known parameter fitting problem. Evolutionary algorithms are powerful methods for finding solutions to optimisation problems with large search spaces, such as the parameter fitting problem mentioned. In this talk we’ll present a framework bringing together evolutionary computation techniques with modelling using process algebra to provide numeric parameters for predefined models. The tuned models can then be used confidently for further simulation or analysis. Moreover, further insight into the system under investigation may be gained by examining the performance of the evolutionary algorithm. The Evolving Process Algebra (EPA) framework will be demonstrated through benchmark examples from systems biology or computer science. This is joint work with David Cairns and David Marco at Stirling.
School of Computing, Robert Gordon University, St Andrew Street, Aberdeen, Lecture Room C48, 14:15 – 15:15.