An Implementation of Machine Learning Systems using Fuzzy Distributed Artificial Intelligent Systems

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Author(s) M.Kumarasamy | A.Jebaraj Ratnakumar
Pages 1422-1425
Volume 2
Issue 8
Date August, 2012
Keywords Fuzzy logic, Artificial Intelligence, Neural Networks, Machine Learning


The main goal of this paper is to develop machine learning systems using fuzzy distributed artificial intelligent systems. The goal of machine learning is to ensemble learning and adaptation abilities of living species in computers; more deeply to program computers to use past experience to solve a given problem. As also stated by Michalski: “Learning is constructing or modifying representations of what is being experienced.” In general, machine learning refers to a system capable of the autonomous acquisition and integration of knowledge. Nowadays many powerful methods with different roots, has been introduced in ML such as: neural networks, genetic algorithms, genetic programming, fuzzy logic and also many hybrid approaches as a combination of some aforementioned ones. Using Machine Learning with Fuzzy techniques we implement Fuzzy Q Learning Algorithm.

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