Paper Info
Title
Artificial Hormone Reaction Networks: Towards Higher Evolvability in Evolutionary Multi-Modular Robotics
Abstract
The semi-automatic or automatic synthesis of robot controller software is both desirable and challenging. Synthesis of rather simple behaviors such as collision avoidance by applying artificial evolution has been shown multiple times. However, the difficulty of this synthesis increases heavily with increasing complexity of the task that should be performed by the robot. We try to tackle this problem of complexity with Artificial Homeostatic Hormone Systems (AHHS), which provide both intrinsic, homeostatic processes and (transient) intrinsic, variant behavior. By using AHHS the need for pre-defined controller topologies or information about the field of application is minimized. We investigate how the principle design of the controller and the hormone network size affects the overall performance of the artificial evolution (i.e., evolvability). This is done by comparing two variants of AHHS that show different effects when mutated. We evolve a controller for a robot built from five autonomous, cooperating modules. The desired behavior is a form of gait resulting in fast locomotion by using the modules' main hinges.
Year
Venue
Keywords
2010
ALIFE
evolutionary computing,artificial intelligent,artificial evolution
DocType
Volume
ISSN
Journal
abs/1011.3912
Artificial Life XII (ALife XII), Odense, Denmark, pp. 773-780, MIT Press, 2010
Citations 
PageRank 
References 
12
0.73
11
Authors
4
Name
Order
Citations
PageRank
Heiko Hamann131742.00
Jürgen Stradner2605.33
Thomas Schmickl352454.83
Karl Crailsheim428426.24