Turtles, termites, and traffic jams: explorations in massively parallel microworlds
Turtles, termites, and traffic jams: explorations in massively parallel microworlds
Understanding intelligence
Being There: Putting Brain, Body, and World Together Again
Being There: Putting Brain, Body, and World Together Again
Cooperative Mobile Robotics: Antecedents and Directions
Autonomous Robots
Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines
Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines
YARS: A Physical 3D Simulator for Evolving Controllers for Real Robots
SIMPAR '08 Proceedings of the 1st International Conference on Simulation, Modeling, and Programming for Autonomous Robots
Evolving morphology and control: a distributed approach
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
50 years of artificial intelligence
Neural control of a modular multi-legged walking machine: Simulation and hardware
Robotics and Autonomous Systems
Hi-index | 0.00 |
Using decentralized control structures for robot control can offer a lot of advantages, such as less complexity, better fault tolerance and more flexibility. In this paper the evolution of recurrent artificial neural networks as centralized and decentralized control architectures will be demonstrated. Both designs will be analyzed concerning their structure-function relations and robustness against lesion experiments. As an application, a gravitationally driven robotic system will be introduced. Its task can be allocated to a cooperative behavior of five subsystems. A co-evolutionary strategy for generating five autonomous agents in parallel will be described.