Wi!Mi Expert System Shell as the Novel Tool for Building Knowledge-Based Systems with Linear Computational Complexity
(*) Corresponding author
Expert systems (ES) are very effective tools for solving various complex problems, which usually require human intelligence. In fact, these systems emulate a human expert's decision-making process. However, development of various ESs from scratch is a tedious and costly process. This article describes a novel ES building tool. This tool belongs to the class of the so-called Wi!Mi ES shells–programs that allow significantly simplify and accelerate the ES development process. It uses a new knowledge representation model, which is based on the bipartite graphs as well as on the significantly improved but simple inference engine. This tool makes it possible to process large systems involving millions of variables during several seconds. This article presents both theoretical basis and inner workings of the Wi!Mi tool, as well as several examples of various subject domains. Finally, this tool is evaluated by testing on the prototype including up to 3 million variables and rules.
Copyright © 2018 Praise Worthy Prize - All rights reserved.
F. G. Luger, Artificial Intelligence: Structure and Strategies for Complex Problem Solving (Boston: Pearson, 2009).
S. J. Russel, and P. Norvig, Artificial Intelligence: a Modern Approach (3rd ed.) (Boston: Pearson, 2010).
P. D. Antonov, M. O. Chibirova, E. A. Zhdanovich, G. S. Sergushin, and D. V. Eliseev, A Practical Example of Using the Mivar Approach to Create an Expert System in the Domain of "Geometry", Radio Industry, Vol. 3: 131-145, 2015. (in Russian).
Tool for Building Expert Systems, 2000. Retrieved 11 16, 2017, from http://clipsrules.sourceforge.net
I. Bratko, Prolog Programming for Artificial Intelligence (4th ed.) (Pearson Education Canada, 2012).
Analytic Technologies, 2010. Retrieved 11 16, 2017, from http://www.fico.com/en/predictive-analytics/analytic-technologies/rules-based-systems
Expert System Development Tool, 2011. Retrieved from http://www.exsys.com/exsyscorvid.html Accessed 17.11.16.
H. E. Friedman, Jess in Action: Java Rule-Based System (Greenwich: Manning Publications, 2003).
O. O. Varlamov, Linear Matrix Method for Determining a Route on the Adaptive Network of Rules, Proceedings of the Universities, Electronics, Vol. 6: 48-53, 2002a. (In Russian).
O. O. Varlamov, Evolutionary Databases and Knowledge for Adaptive Synthesis of Intelligent Systems, The Mivar Information Space (Moscow: Radio & Communication, 2002b).
M. O. Chibirova, Structural Development of the Mivar Approach: Classes and Relations, Radio industry, Vol.3: 44-54, 2015.
O. O. Varlamov, The Role and Place of the Mivars in Computer Science, Artificial Intelligence, and Computer Science, Radio industry, Vol. 3: 10-27, 2015.
O. O. Varlamov, M. O. Chibirova, A. M. Khadiev, P. D. Antonov, S. S. Sergushin, I. A. Shoshev, and K. V. Nazarov, Workshop on the Creation of Mivar Expert Systems, Textbook (Moscow, Russian Federation: "Belyi veter", М., 2016).
V. Cacchiani, D. Huisman, M. Kidd, L. Kroon, P. Toth, L. Veelenturf & J. Wagenaar, An Analysis of Recovery Models and Algorithms for the Real-Time Railway Rescheduling, Transportation Research Part B: Methodological, Vol. 63: 15-37, 2014.
O. O. Varlamov, System Analysis and Synthesis of the Data Models and Methods of Information Processing in the Self-Organizing Complexes of the Operational Diagnostics (Dissertation for the degree of Doctor of Technical Sciences. Moscow, 2003).
K. Jo, J. Kim, D. Kim, C. Jang, M. Sunwoo, Development of the Autonomous Car—Part II: A Case Study on the Implementation of the Autonomous Driving System Based on Distributed Architecture, IEEE Transoperations on Industrial Electronics, Vol. 62(Issue 8), 5119-5132, 2015.
O. O. Varlamov, R. A. Sandu, A. N. Vladimirov, A. V. Nosov, and M. L. Overchuk, The Mivar Approach to the Creation of the Multi-Subject Active Expert Systems for Izvestiya SFU, Technical science, Vol.11 (Issue112): 226-232, 2010.(in Russian).
O. O. Varlamov, V. M. Lazarev, D. A. Chuvikov, and P. Jha, On the Prospects for the Creation of the Autonomous Intelligent Robots Based on the Mivar Technologies", RadioIndustry, vol. 4: 96-105, 2016. (in Russian).
E. A. Zhdanovich, P. K. Chernyshev, K. A. Yufimychev, D. V. Eliseev, and D. A. Chuvikov,Calculation of the Arbitrary Algorithms for Functioning of Service Robots on the Basis of the Mivar Approach, Radio industry, Vol. 3: 226-242, 2015.
S. S. Shadrin, A. M. Ivanov, and D. V. Nevzorov, Autonomous Wheeled Vehicle as a Part of the Intelligent Transport Systems, Natural and technical sciences, Vol. 6 (Issue 84): 309-311, 2015. (in Russian).
S. S. Shadrin, O. O. Varlamov, and A. M. Ivanov, Experimental Autonomous Road Vehicle with Logical Artificial Intelligence, Journal of Advanced Transportation, Vol. 2017: 10, 2017.
R. O. Duda, and E. H. Shortliffe, Expert Systems Research, Science, Vol. 220: 261-268, 1993.
J. C. Giarratano, and G. D. Riley, Expert Systems: Principles and Programming. (4th ed.) (Course Technology, 2004).
Jess, Retrieved from question, 1999:
http://www.jessrules.com/jess/FAQ.shtml Accessed 17.11.17
Gensym. Real-Time Management of the Mission-Critical Systems, 2017. Retrieved from http://www.gensym.com/
R. T. Plant, and J. P. Salinas, Expert Systems Shell Benchmarks: the Missing Comparison Factor, Expert Systems, Vol.27: 89-101, 1994.
R. Davis, H. Shrobe, and P. Solovits, What is a Knowledge Representation?, AI Magazine, Vol.141: 17-33, 1993.
G. Nebel, and B. Lakemeyer, Foundation of Knowledge Representation and Reasoning (Boston: Pearson, 2009).
O. O. Varlamov, MIVAR: Transition from Productions to the Bipartite Graphs of the MIVAR Nets and Practical Realization of the Automated Constructor of Algorithms, 2017.
P. A. Jaquesa, H. Seffin, G. Rubi, F. De Morais, C. Ghilardi, I. Bittencourt, and S. Isotani, The Rule-Based Expert Systems to Support the Step-by-Step Guidance in the Algebraic Problem Solving, Expert Systems with Applications, Vol. 40 (Issue 14): 5456-5465, 2013.
E. A. Zhdanovich, P. A. Antonov, A. M. Khadiev, G. S. Sergushin, and M. O. Chibirova, The Diagnosis of the Symptoms on the Basis of the Mivar Approach, Radio industry, Vol. 3: 122-130, 2015.
- There are currently no refbacks.
Please send any question about this web site to firstname.lastname@example.org
Copyright © 2005-2023 Praise Worthy Prize