Agent technologies: hybrid intelligent systems
Main Article Content
Abstract
The current paper presents the survey of investigations on developing hybrid intelligent systems as a tool for solution of complex problems. The specific features of developing hybrid intelligent systems algorithmic and structural building are analyzed, classification schemes are given, the stages of building developing hybrid intelligent systems are discussed, and the role of they implementations with the use of agents are pointed out in the paper
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
References
N. Viner, Cybernetics, or management andthe connection between an animal and a car, Moscow: Sov. radio, 1968, p. 328.
A. Ivakhnenko, Y. Zaichenko, and V. Dymitrov, Decision-making based on self-organization, Moscow: Sov. radio, 1976, p. 280.
A. Feldbaum, Basics of the theory of optimalof automatic systems, Moscow: Nauka, 1966, p. 623.
Tsypkin Y.Z., Adaptation and training in the cartechnical systems, Moscow: Nauka, 1968, p. 400.
U. Ashby, The structure of the brain. Originadaptive behavior, Moscow: Izd-vo inostr.lit-ry, 1962, p. 400.
[1]S. Russell and P. Norvig, Iskusstvennyjintelligence Modern approach, Moscow: Williams, 2003, p. 1408.
S. Goonatilake, J. A. Campbell, and N. Ahmad, “Genetic-fuzzy systems for financial decision making”, in Advances in Fuzzy Logic, Neural Networks and Genetic Algorithms, Berlin, Heidelberg: Springer Berlin Heidelberg, 1995, pp. 202–223. DOI:10.1007/3-540-60607-6_14
M. Wooldridge, N. R. Jennings, and D. Kinny, Autonomous Agents and Multi-Agent Systems, vol. 3, no. 3, pp. 285–312, Jan. 2000. DOI:10.1023/A:1010071910869
N. R. Jennings, “On agent-based software engineering”, Artificial Intelligence, vol. 117, no. 2, pp. 277–296, Mar. 2000. DOI:10.1016/S0004-3702(99)00107-1
G. Booch, Object-Oriented Analysis and Design withApplications, Addison Wesley, 1994, p. 650.
D. C. Lee and K. W. Lee, “Design and Implementation of Multi-Agents for Learner-oriented Course Scheduling on the Internet”, in E-Service Intelligence, Berlin, Heidelberg: Springer Berlin Heidelberg, 2007, pp. 601–626. DOI:10.1007/978-3-540-37017-8_28
L. Zadeh, The roles of fuzzy logic and softcomputing in the conception, design and deploymentof intelligent systems, Berlin: Springer-Verlag, 1997, p. 183.
H. Simon, The Sciences of the Artificial, MITPress, 1966, p. 412.
F. Bergenti, M.-P. Gleizes, and F. Zambonelli, Methodologies and Software Engineeringfor Agent Systems. The Agent-Oriented SoftwareEngineering Handbook, Kluwer AcademicPublishers, 2004, p. 505.
N. Jennings and M. Wooldridge, “Agent-OrientedSoftware Engineering”, Handbook of AgentTechnologies, pp. 180–196, Jan. 2001.
M. Wooldridge, “Agent-based software engineering”, IEE Proceedings - Software Engineering, vol. 144, no. 1, p. 26, Jan. 1997. DOI:10.1049/ip-sen:19971026
J. Von Neumann and O. Morgenstern, Theory of Games and Economic Behavior, New Jersey: Princeton University Press, 1944, p. 512.
E. H. Durfee and V. R. Lesser, “Negotiating Task Decomposition and Allocation Using Partial Global Planning”, in Distributed Artificial Intelligence, Elsevier, 1989, pp. 229–243. DOI:10.1016/B978-1-55860-092-8.50014-9
N. R. Jennings, K. Sycara, and M. Wooldridge, Autonomous Agents and Multi-Agent Systems, vol. 1, no. 1, pp. 7–38, Jan. 1998. DOI:10.1023/A:1010090405266
G. Weiss, Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, MIT Press, 1999, p. 480.
N. R. Jennings, “An agent-based approach for building complex software systems”, Communications of the ACM, vol. 44, no. 4, pp. 35–41, Apr. 2001. DOI:10.1145/367211.367250
L. Medsker and D. Bailey, Models and Guidelines for Integrating Expert Systems and Neural Networks Hybrid Architectures for Intelligent Systems, CRC Press, 1992, pp. 154–171.
L. R. Medsker, Hybrid Intelligent Systems, Boston, MA: Springer US, 1995. DOI: 10.1007/978-1-4615-2353-6
L. Wang, S. Balasubramanian, and D. Norrie, Agent-based Intelligent Control System Design for Real-time Distributed Manufacturing Environments Working Notes of the Agent-Based Manufacturing Workshop, Minneapolis: MN, 1998, pp. 152–159.
D. C. Lee and K. W. Lee, “Design and Implementation of Multi-Agents for Learner-oriented Course Scheduling on the Internet”, in E-Service Intelligence, Berlin, Heidelberg: Springer Berlin Heidelberg, 2007, pp. 601–626. DOI:10.1007/978-3-540-37017-8_28
