EDA MULTI-AGENT MODEL FOR ORGANIZATIONAL DOMAINS
The aim is to establish a framework for the development of social orientation agents. We assume that the social orientation of the organization is related to the multi-agent interac tions, which in turn implies the exchange of information, or dynamically (via connection) or statically (via society or culture) based on the standards of various types (perception, cognition, behavior, evaluation). As the «information» is difficult to formalize the term, preference is given to the concept of «semiotics», which uses a «sign» as a basic concept. The information provided in the form of a composition of characters is analyzed at various levels, including the syntax, semantics, pragmatics and social level. Based on the various properties of signs available in different semiotic levels, we propose a new agent-based model based on the principles of «Epistemic-Deontic-Axiological»,to represent the information agent states and at the same time defining its conceptual environment interactions . EDA-agents are intended to describe social behavior.
The studies were conducted in the framework of the grant Russian Foundation for Basic Research 12-07-00797.
Multi-agent modeling, organizational semiotics, distributed artificial intelligence, epistemic component, deontic component, axiological component, ontology.
Issue number: 7
UDK: 004.942, 004.853, 721.021.23, 519.876.5
Authors: Kulyanitsa A. L., Fomicheva O. E.
About authors: Kulyanitsa A. L., Doctor of Technical Sciences, Professor
Fomicheva O. E., Candidate of Technical Sciences, Assistant Professor,
Institute of Information Technologies and Automated Control Systems,
National University of Science and Technology «MISiS»,
119049, Moscow, Russia.
REFERENCES: 1. Stamper R. Information in Business and Administrative Systems. John Wiley & Sons, 1973.
2. Liu K. Semiotics Information Systems Engineering. Cambridge University Press. Cambridge, 2000.
3. Brewka G. Reasoning about Priorities in Default Logic. In Proceedings of AAAI-94, AAAI Press, Seattle, USA, 1994.
4. Fred A., Filipe J. Syntax-Directed Translation Schemes For Multi-Agent Systems Conversation Modeling. Submitted to ICEIS 2000, Stafford, UK, 2000.