Title :
How to autonomously decide boundary between self and others?
Author :
Takadama, Keiki ; Inoue, Hiroyasu ; Shimohara, Katsunori
Author_Institution :
ATR Int., Kyoto, Japan
Abstract :
This paper extends the learning classifier system. (LCS) to introduce the mechanism for recognizing a current situation by determining a boundary between self and others, and investigates its effectiveness in an interaction with an agent. Intensive simulations for adapting an interacting agent by acquiring its internal model have revealed the following implications: (1) the proposed mechanism. gives a higher adaptation to the integrating agent than a random mechanism, the conventional LCS, and previously proposed mechanisms; (2) the proposed mechanism keeps its effectiveness, even in a complex internal model of an. agent; and (3) the proposed mechanism has the potential to provide autonomy in terms of the precise recognition of the current situation
Keywords :
adaptive systems; learning (artificial intelligence); learning systems; pattern classification; simulation; software agents; agent; autonomous boundary decision; complex internal model; current situation recognition; interacting agent adaptation; internal model; learning classifier system; simulations; Cost accounting; Humans; Inference mechanisms; Production systems; Zero current switching;
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.2000.972459