Title :
Learning of multiple robots in quasi-ecosystem
Author :
Kubota, Naoyuki ; Ogishi, Masato ; Kojima, Fumio
Author_Institution :
Dept. of Human & Artificial Intelligent Syst., Fukui Univ., Japan
Abstract :
This paper deals with multiple robots in quasi-ecosystem. An ecosystem model composed of insects and plants, which are in a relationship of parasitism, is simulated on the discrete cell space. In this ecosystem, the plants become easy to be eliminated as the population size of the insects increases. Consequently, it is required to maintain the species of plants in the quasi-ecosystem. Therefore, multiple robots are introduced to remove some insects from the quasi-ecosystem. However, if the robots eliminate all of insects, the viruses will eliminate the plants owing to diseases. In this ecosystem with complicated relationship, the robots should acquire strategies to maintain plants. In this paper, we apply a neural network for learning a strategy for removing insects. Furthermore, we show several simulation results of behavior learning of robots. Finally, we demonstrate a simple experiment of robots
Keywords :
cellular automata; learning (artificial intelligence); multi-robot systems; neural nets; cellular automata; discrete cell space; insects; multiple robot learning; neural network; parasitism; plants; quasi-ecosystem; viruses; Automata; Ecosystems; Humans; Insects; Intelligent robots; Intelligent systems; Lattices; Neural networks; Orbital robotics; Viruses (medical);
Conference_Titel :
Industrial Electronics Society, 2000. IECON 2000. 26th Annual Confjerence of the IEEE
Conference_Location :
Nagoya
Print_ISBN :
0-7803-6456-2
DOI :
10.1109/IECON.2000.972601