Title :
Evaluation of genetic-fuzzy systems in the configuration space
Author :
Bonarini, Andrea ; Fiorellato, Fabio
Author_Institution :
Dipt. di Elettronica e Inf., Politecnico di Milano, Italy
Abstract :
We propose an approach to ground the design of learning systems on the analysis of the configuration space of the learning device (e.g., a robot) and on the interpretation of input data. We focus on learning fuzzy classifier systems adopted to evolve behavioral controllers for autonomous robots. We show how it is possible to define some indexes to evaluate objectively both the learning process and the evolved system, thus supporting their designing with engineering principles
Keywords :
fuzzy logic; fuzzy systems; genetic algorithms; learning (artificial intelligence); learning systems; mobile robots; autonomous robots; behavioral controllers; configuration space; evolutionary robotics; fuzzy rule bases; genetic algorithms; genetic-fuzzy systems; input data interpretation; learning fuzzy classifier systems; learning systems; mobile robots; reinforcement learning; Artificial intelligence; Autonomous agents; Design engineering; Fuzzy systems; Genetics; Ground support; Learning systems; Orbital robotics; Robot control; Systems engineering and theory;
Conference_Titel :
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-7078-3
DOI :
10.1109/NAFIPS.2001.944783
