Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm
Paechter, B. (2016). Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm. In: Handl, J.,
Lewis, Peter R.,
Paechter, B. (Eds.) Parallel Problem Solving from Nature – PPSN XIV, , () ( ed.). (pp. ). : . Springer International Publishing.
It is well known that in open-ended evolution, the nature of the environment plays in key role in directing evolution. However, in Evolutionary Robotics, it is often unclear exactly how parameterisation of a given environment might influence the emergence of particular behaviours. We consider environments in which the total amount of energy is parameterised by availability and value, and use surface plots to explore the relationship between those environment parameters and emergent behaviour using a variant of a well-known distributed evolutionary algorithm (mEDEA). Analysis of the resulting landscape show that it is crucial for a researcher to select appropriate parameterisations in order that the environment provides the right balance between facilitating survival and exerting sufficient pressure for new behaviours to emerge. To the best of our knowledge, this is the first time such an analysis has been undertaken.
Director of CEC
+44 131 455 2783
+44 131 455
Director of Research
+44 131 455 2764
Areas of Expertise
See all areas of expertise
The Bio-Inspired Algorithms group within the Centre for Algorithms, Visualisation and Evolving Systems is a large and thriving group with interests in nature-inspired computing that include Evolutionary Computing, Hyper-Heuristics, Artificial Immune Systems and Swarm Intelligence.