Making Organizational Learning Operational: Implications from Learning Classifier Systems

Keiki Takadama (), Takao Terano (), Katsunori Shimohara (), Koichi Hori () and Shinichi Nakasuka ()
Additional contact information
Keiki Takadama: ATR Human Information Processing Research Labs
Takao Terano: Univ. of Tsukuba
Katsunori Shimohara: ATR Human Information Processing Research Labs
Koichi Hori: Univ. of Tokyo
Shinichi Nakasuka: Univ. of Tokyo

Computational and Mathematical Organization Theory, 1999, vol. 5, issue 3, No 3, 229-252

Abstract: Abstract The concepts of organizational learning in organization and management science cover a very wide range of organization-related activities in organization. Since socially situated intelligence is one of such activities, this paper makes the concept of organizational learning operational from the computational viewpoint for investigating socially situated intelligence. In particular, this paper focuses on the characteristics of multiagent learning as one kind of socially situated intelligence, and analyzes them using four operationalized learning mechanisms in organizational learning. A careful investigation on the characteristics of multiagent learning has revealed the following implications: (1) there are two levels in the learning mechanisms for multiagent learning (the individual level and organizational level) and each mechanism is divided into two types (single- and double-loop learning). The integration of these four learning mechanisms improves socially situated intelligence; and (2) the following properties support socially situated intelligence: (a) different dimensions in learning mechanisms, (b) interaction among various levels and types of learning mechanisms in addition to interaction among agents, and (c) combination of exploration at an individual level and exploitation at an organizational level.

Keywords: socially situated intelligence; organizational learning; multiagent learning; learning classifier system (search for similar items in EconPapers)
Date: 1999
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1023/A:1009638423221 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:comaot:v:5:y:1999:i:3:d:10.1023_a:1009638423221

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10588

DOI: 10.1023/A:1009638423221

Access Statistics for this article

Computational and Mathematical Organization Theory is currently edited by Terrill Frantz and Kathleen Carley

More articles in Computational and Mathematical Organization Theory from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().