Designing Sociable Robots
Old tricks, new dogs: ethology and interactive creatures
Old tricks, new dogs: ethology and interactive creatures
The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind
The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind
Evolutionary generative process for an artificial creature's personality
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Genetic algorithms and artificial life
Artificial Life
Journal of the ACM (JACM)
Reinforcement learning based resource allocation in business process management
Data & Knowledge Engineering
The incremental method for fast computing the rough fuzzy approximations
Data & Knowledge Engineering
Function meets style: insights from emotion theory applied to HRI
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
| Hi-index | 0.00 |
This paper proposes a way to generate a robot genome that contributes to defining the personality of a software robot or an artificial life in a mobile phone. The personality should be both complex and feature-rich, but still plausible by human standards for an emotional life form. However, it becomes increasingly difficult and time-consuming to ensure reliability, variability and consistency for the robot's personality while manually initializing values for the individual genes. To overcome this difficulty, this paper proposes a neural network algorithm for a genetic robot's personality (NNGRP) and an upgraded version of a previously introduced evolutionary algorithm for a genetic robot's personality (EAGRP). The robot genomes for heterogeneous personalities are demonstrably generated via the NNGRP and the EAGRP and compared. The implementation is embedded into genetic robots in a mobile phone to verify the feasibility and effectiveness of each algorithm.