The TD methods, were further compared to variants of NEAT and HyperNEAT (that is, OS, ONS, NS, OGN and GNS) with and without behavior transfer. The results demonstrated that the ONS variant of HyperNEAT performs much better (with respect to effectiveness and efficiency) than both TD methods and all variants of NEAT. Specific
evolutionary search methods to direct NE such as behavior diversity maintenance and the hybrid approach, work most effectively at balancing exploration versus exploitation in the search space, more so than TD methods.
Evolutionary search approaches investigated were objective-based search (OS), novelty search (NS), genotypic diversity search (GNS), hybrid of objective and novelty search and hybrid of objective based and genotypic diversity maintenance search (ONS and OGN, respectively). In this thesis, three methodological features were explored to ascertain an appropriate combination that enables the evolution of high quality solutions based on effectiveness (task performance) and efficiency (speed of adaptation) of evolved behaviors. These features are as follows: First, direct versus indirect encoding neuro-evolution methods for collective behavior evolution (that is, NEAT and HyperNEAT, respectively). Second, non-objective evolutionary search versus objective based search approach for guiding collective behavior evolution. Third, neuro-evolution with collective behavior transfer.
“with behavior transfer” referring more or less to crossover/mutate rather than starting from scratch with new individuals. Something like that.