Session details: Workshop: symbolic regression and modelling

Abstract

It is our great pleasure to welcome you to the 6th 2014 GECCO Workshop on Symbolic Regression and Modeling. Over the past five workshops, we have had interesting presentations and fantastic discussions around symbolic regression, genetic programming, and the increasing demands and opportunities to impact science and industry. The workshop has spawned new research and lead to many new collaborations. We are looking forward to another great workshop with four accepted papers and one invited talk. Symbolic Regression and Modeling is used to designate the search for symbolic descriptions, usually in the language of mathematics, to describe and predict numerical data in diverse fields such as industry, economics, finance and science. Symbolic modeling captures the field of symbolic regression: a genetic programming based search technique for finding symbolic formulae on numerical data in order to obtain an accurate and concise description of that data in symbolic, mathematical form. In the evolutionary computation field it also captures learning classifier systems, if and when they are applied to obtain specific interpretable results in the field of interest. The key discriminator of producing symbolic results over numerical results is the ability to interpret and analyze the results, leading either to acceptance by field experts, or to heightened understanding of the theory in the field of application. Interpretation is key, and the workshop will focus heavily on this. The workshop will focus on advances in using symbolic modeling for real world problems in industry, economics, finance and science. The invited talk to be presented at the workshop is by David Medernach from the University on the topic of training data sampling approaches in symbolic regression modeling.