Managing team-based problem solving with symbiotic bid-based genetic programming

Bid-based Genetic Programming (GP) provides an elegant mechanism for facilitating cooperative problem decomposition without an a priori specification of the number of team members. This is in contrast to existing teaming approaches where individuals learn a direct input-output map (e.g., from exemplars to class labels), allowing the approach to scale to problems with multiple outcomes (classes), while at the same time providing a mechanism for choosing an outcome from those suggested by team members. This paper proposes a symbiotic relationship that continues to support the cooperative bid-based process for problem decomposition while making the credit assignment process much clearer. Specifically, team membership is defined by a team population indexing combinations of GP individuals in a separate team member population. A Pareto-based competitive coevolutionary component enables the approach to scale to large problems by evolving informative test points in a third population. The...

• Type: Conference
• Year: 2008
• Where: GECCO
• Authors: Peter Lichodzijewski, Malcolm I. Heywood
• Keywords: GECCO 2008, Optimization, Problem Decomposition, SBB Classifiers, Team Member