Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines
Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines
Emergence of Collective Behavior in Evolving Populations of Flying Agents
Genetic Programming and Evolvable Machines
Combining Simulation and Reality in Evolutionary Robotics
Journal of Intelligent and Robotic Systems
Behavior-based speciation for evolutionary robotics
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Evolving teamwork and coordination with genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
HyperNEAT controlled robots learn how to drive on roads in simulated environment
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
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Theory of Mind (ToM) is the ability to read another person's mind. To apply ToM in robots, robot should read the intention from target. However, it is difficult to read target's intention directly. Robot uses the sensors to measure distance from target because distance is the feature to read target's intention. Neural network has been widely used to control the robot for generating a diverse speciation. It has been less explored in behavior-based robotics. Speciation usually relies on a distance measure that allows different from the robot to target to be compared. In this paper, we proposed novel measure to generate diverse behaviors of a robot with speciation for ToM. It includes some distance measure such as Euclidean distance, cosine distance, arctangent distance, and edit distance. It generates diverse behaviors of the robot by neural network for ToM. The proposed method has been experimented on a real e-puck robot platform.