This paper investigates incremental multiagent learning in static or evolving structured networks. Learning examples are incrementally distributed among the agents, and the object...
Gauvain Bourgne, Amal El Fallah-Seghrouchni, Henry...
The possible application of evolving artificial embryos to build functional machinery is a promising area of research. Unfortunately, there are still many fundamental problems to ...
Felix Streichert, Christian Spieth, Holger Ulmer, ...
We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation...
Ontologies are heavily used in life sciences and evolve continuously to incorporate new or changed insights. Often ontology changes affect only specific parts (regions) of ontologi...
Michael Hartung, Anika Gross, Toralf Kirsten, Erha...
This paper investigates the evolution of autonomous agents that solve a memorydependent counting task. Two types of neurocontrollers are evolved: networks of McCulloch-Pitts neuro...