Add to ORKGThis paper investigates a system that uses a genetic algorithm to train a robot for a generalised test environment, then an evolutionary strategy to investigate the effect of continuing the evolution as the robot progresses with its task. The paper concludes that continuing evolution after a training phase has an important role to play in producing truly adaptive robots
Abstract Our experiences with a range of evolutionary robotic experiments have resulted in major cha...
A review is given on the use of evolutionary techniques for the automatic design of adaptive robots....
Evolutionary algorithms incorporate principles from biological population genetics to perform search...
This paper investigates a system that uses a genetic algorithm to train a robot for a generalised te...
A central aim of robotics research is to design robots that can perform in the real world; a real wo...
For many years, researchers in the field of mobile robotics have been investigating the use of genet...
This thesis investigates the use of Genetic Programming (GP) to evolve controllers for an autonomous...
After reviewing current approaches in Evolutionary Robotics, we point to directions of research that...
This paper takes a critical look at the concept of real-world robot evolution discussing specific ch...
Inspired by animals’ ability to learn and adapt to changes in their environment during life, hybrid ...
A review is given on the use of evolutionary techniques for the automatic design of adaptive robots....
Artificial evolution as a design methodology allows the relaxation of many of the constraints that h...
This book presented techniques and experimental results which have been pursued for the purpose of e...
We use genetic algorithms to evolve behavioral properties of simulated autonomous vehicles. The trai...
Through series of experiments this work compares effects of different types of genetic algorithms on...
Abstract Our experiences with a range of evolutionary robotic experiments have resulted in major cha...
A review is given on the use of evolutionary techniques for the automatic design of adaptive robots....
Evolutionary algorithms incorporate principles from biological population genetics to perform search...
This paper investigates a system that uses a genetic algorithm to train a robot for a generalised te...
A central aim of robotics research is to design robots that can perform in the real world; a real wo...
For many years, researchers in the field of mobile robotics have been investigating the use of genet...
This thesis investigates the use of Genetic Programming (GP) to evolve controllers for an autonomous...
After reviewing current approaches in Evolutionary Robotics, we point to directions of research that...
This paper takes a critical look at the concept of real-world robot evolution discussing specific ch...
Inspired by animals’ ability to learn and adapt to changes in their environment during life, hybrid ...
A review is given on the use of evolutionary techniques for the automatic design of adaptive robots....
Artificial evolution as a design methodology allows the relaxation of many of the constraints that h...
This book presented techniques and experimental results which have been pursued for the purpose of e...
We use genetic algorithms to evolve behavioral properties of simulated autonomous vehicles. The trai...
Through series of experiments this work compares effects of different types of genetic algorithms on...
Abstract Our experiences with a range of evolutionary robotic experiments have resulted in major cha...
A review is given on the use of evolutionary techniques for the automatic design of adaptive robots....
Evolutionary algorithms incorporate principles from biological population genetics to perform search...