Fuzzy Complex Assessment of Activities of the Agent in Multi-Agent System
In article the technique of an fuzzy complex assessment of the agent in multi-agent system from a line item of efficiency of his activities is considered. It is set that overall performance of the agent depends on three principal components: level of professional competence of the agent, his personal qualities and emotional background. In a technique the approach integrating both expert estimates, and the actual data about results of operation of the agent in system is applied. The system of the indices which are best characterizing separate aspects of activity of the agent in multi-agent system is offered. At the same time the key characteristic is the level of his professional competence. The fuzzy complex assessment of activities of the agent in system gives the chance to reveal more and less effective agents that is important for further acceptance of administrative decisions.
KeywordsMulti-agent system Intelligent agent Efficiency of activities Iinguistic variable Fuzzy logic Expert estimates
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- 1.Mohammed Mekidiche, Mostefa Belmokaddem, “Application of Weighted Additive Fuzzy Goal Programming Approach to Quality Control System Design”, IJISA, vol. 4, no. 11, pp. 14 – 23, 2012. DOI: 10.5815/ijisa.2012.11.02.
- 2.Haiying Ren, Siwei Li, “A Heterogeneous Agent-based Asset Pricing Model and Simulation”, IJEM, vol. 2, no. 4, pp. 9 – 18, 2012. DOI: 10.5815/ijem.2012.04.02.
- 3.E.V. Krishnamurthy, “Agent-based Models in Synthetic Biology: Tools for Simulation and Prospects”, IJISA, vol.4, no.2, pp. 58 − 65, 2012. DOI: 10.5815/ijisa.2012.02.07.
- 4.Mohammed Abbas Kadhim, M. Afshar Alam, Harleen Kaur,”A Multi-intelligent Agent System for Automatic Construction of Rule-based Expert System”, Interna tional Journal of Intelligent Systems and Applications(IJISA), Vol.8, No.9, pp.62-68, 2016. DOI: 10.5815/ijisa.2016.09.08
- 5.Purba D. Kusuma, Azhari, Reza Pulungan,”Agent-Based Buyer-Trader Interaction Model of Traditional Markets”, International Journal of Intelligent Systems and Applications(IJISA), Vol.8, No.11, pp.1-8, 2016. DOI: 10.5815/ijisa.2016.11.01
- 6.Satyendra Singh Chouhan,Rajdeep Niyogi, “An Analysis of the Effect of Communication for Multi-agent Planning in a Grid World Domain”, IJISA, vol. 4, no. 5, pp. 8 – 15, 2012. DOI: 10.5815/ijisa.2012.05.02.
- 7.M. Wooldridge, An Introduction to MultiAgent Systems, Chichester: John Wiley & Sons Ltd, 2002. ISBN 0-471-49691-x.Google Scholar
- 8.Burkov, V.N. Theory of the active systems and enhancement of an economic mechanism / V.N. Burkov, V.V. Kondratyev, V.V. Tsyganov, A.M. Cherkashin. M.: Science, 1984. 272 p.Google Scholar
- 9.Burkov, V.N. How to control the organizations / V.N. Burkov, D.A. Novikov. Moscow: “Sinteg”, 2003. 400 p.Google Scholar
- 10.Mutovkina, N.Yu. Methods of the coordinated optimization of modernization of the industrial enterprises: the dissertation for a degree of Candidate of Technical Sciences; specialties 05.13.01, 05.13.10. – Tver: TvGTU, 2009. 219 p.Google Scholar
- 11.Hodashinsky, I.A. Methods of soft estimation of values: monograph / I.A. Hodashinsky. Tomsk: Tomsk state university of management systems and electronics, 2007. 152 p.Google Scholar
- 12.Mutovkina, N.Yu. Behavioral models of intellectual agents in the course of information exchange / N.Yu. Mutovkina, V.N. Kuznetsov, A.Yu. Klyushin // Management systems and information technologies. 2013. No. 1.1 (51), pp. 178 – 183.Google Scholar
- 13.Saati, T. Decision-making. Method of the analysis of hierarchies / T. Saati. M.: Radio and communication, 1993. 278 p.Google Scholar
- 14.Fishburn, P. The theory of usefulness for decision-making / P. Fishburn. M.: Science, 1978. 352 p.Google Scholar
- 15.Mousumi Mitra, Atanu Das, “A Fuzzy Logic Approach to Assess Web Learner’s Joint Skills”, IJMECS, vol. 7, no. 9, pp. 14 – 21, 2015. DOI: 10.5815/ijmecs.2015.09.02.