Open AccessTHE HYBRID AGENT MODEL OF BEHAVIORAL TESTING
Author(s) -
Anna Sugak,
Oleksandr Martynyuk,
Oleksandr Drozd
Publication year - 2015
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.14.4.824
Subject(s) - computer science , component (thermodynamics) , software portability , artificial intelligence , evolutionary algorithm , behavioral modeling , distributed computing , multi agent system , agent based model , intelligent agent , machine learning , physics , thermodynamics , programming language
Operation testing and diagnostic tests, applied for distributed information systems, inherit and employ the properties of distribution, autonomy, goal formation and cooperation, natural for the multi-agent systems. This paper presents the behavioral diagnostics agent model, based on the evolutionary organization of component tests in the automata network environment. The model can be used to construct a multi-agent diagnostics system. A hybrid agent model provides a combination of reactive operation testing and deliberative diagnostic tests, based on the deterministic and evolutionary methods of synthesis of behavioral tests. An agent model consists of the component models of allocation environment, functioning goals and strategies, operations of observation, enforcement strategy and adaptation, initial component models, goals and strategies for ensuring the autonomy. Agent intelligence is based on a locally-exhaustive deterministic and pseudorandom targeted evolutionary synthesis of behavioral tests, providing and accumulating the results. Cooperation of the agents involves their deterministic and evolutionary interactions under the conditions of test feasibility and portability.