Corpus ID: 18043632

Embodied Evolution : A Response toChallenges in Evolutionary

  title={Embodied Evolution : A Response toChallenges in Evolutionary},
  author={RoboticsSevan G. Ficici and Richard A. Watson and Jordan B. Pollack},
We introduce Embodied Evolution (EE), a new methodology for conducting evolutionary robotics (ER). Embodied evolution uses a population of physical robots that evolve by reproducing with one another in the task environment. EE addresses several issues identiied by researchers in the evolutionary robotics community as problematic for the development of ER. We review results from our rst experiments and discuss the advantages and limitations of the EE methodology. 
2 Citations
Embodied Evolution with a New Genetic Programming Variation Algorithm
A new Evolutionary Control System (ECS) able to control a population of mobile robots based on a Genetic Programming algorithm and has two main modules, which are responsible for managing all the evolutionary process in each robot. Expand
Adaptation and Self-adaptation of Developmental Multi-Robot Systems
This work discusses mechanisms, leading to adaptive and self-adaptive behavior, as well as possible conflicts between them, exemplified by a collective locomo - tion of reconfigurable multi-robot system. Expand


Embodied evolution: embodying an evolutionary algorithm in a population of robots
Embodied Evolution is an evolutionary robotics technique that avoids the pitfalls of the simulate-and-transfer method, allows the speed-up of evaluation time by utilizing parallelism, and is particularly suited to future work on multi-agent behaviors. Expand
Evolutionary Robotics: A Survey of Applications and Problems
This paper reviews evolutionary approaches to the automatic design of real robots exhibiting a given behavior in a given environment and its potentialities and limitations. Expand
Explorations in Evolutionary Robotics
Results demonstrate that robust visually guided control systems evolve from evaluation functions that do not explicitly require monitoring visual input, and propose an automatic design process involving artificial evolution, wherein the basic building blocks for evolving cognitive architectures are noise-tolerant dynamical neural networks. Expand
Evolution Versus Design: Controlling Autonomous Robots
  • P. Husbands, I. Harvey
  • Computer Science
  • Proceedings of the Third Annual Conference of AI, Simulation, and Planning in High Autonomy Systems 'Integrating Perception, Planning and Action'.
  • 1992
This paper sets out and justifies a methodology for the development of the control systems, or ‘cognitive architectures)) of autonomous mobile robots. It will be argued that the design b y hand ofExpand
Challenges in evolving controllers for physical robots
The feasibility of applying evolutionary methods to automatically generating controllers for physical mobile robots by describing some of the main approaches and discussing the key challenges, unanswered problems, and some promising directions is discussed. Expand
Automatic creation of an autonomous agent: genetic evolution of a neural-network driven robot
The paper describes the results of the evolutionary development of a real, neural-network driven mobile robot, and shows a number of emergent phenomena that are characteristic of autonomous agents. Expand
Evolution of homing navigation in a real mobile robot
The evolution of a discrete-time recurrent neural network to control a real mobile robot and it is shown that the autonomous development of a set of behaviors for locating a battery charger and periodically returning to it can be achieved by lifting constraints in the design of the robot/environment interactions. Expand
Evolutionary Robotics and the Radical Envelope-of-Noise Hypothesis
New ways of thinking about and building simulations upon which fitness assessments of evolving controllers can be performed are outlined and a potential methodology for building simulations in which evolving controllers are forced to satisfy these conditions if they are to be reliably fit is developed. Expand
Artificial Life and Real Robots
A new abstraction for behavior-based robot programming which is specially tailored to be used with genetic programming techniques is introduced, which will be necessary to automatically evolve programs that are one to two orders of magnitude more complex than those previously reported in any domain. Expand
Half-baked, Ad-hoc and Noisy: Minimal Simulations for Evolutionary Robotics
A theoretical framework and formal language for understanding how simple, fast simulations can be used to evolve controllers for real robots is put forward and techniques are derived for ensuring that controllers which evolve to be reliably reliable within a simulation will transfer into the real world. Expand