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Bioinformatics with Evolutionary Computation
This chapter makes the presumption that it is more important to understand the domain of the problem of interest and to pursue the best achievable...
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Rough Set Theory with Applications to Data Mining
This paper is an introduction to rough set theory with an emphasis on applications to data mining. First, consistent data are discussed, including...
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Reinforcement Learning: A Brief Overview
Learning techniques can be usefully grouped by the type of feedback that is available to the learner. A commonly drawn distinction is that between...
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An Analysis of Continuous-Valued Representations for Learning Classifier Systems
Learning Classifier Systems [11] typically use a ternary representation to encode the environmental condition that a classifier matches. However,...
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Data Driven Fuzzy Modelling with Neural Networks
Extraction of models for complex systems from numerical data of behavior is studied. In particular, systems representable as sets of fuzzy if-then...
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On the Classification of Maze Problems
A maze is a grid-like two-dimensional area of any size, usually rectangular. A maze consists of cells. A cell is an elementary maze item, a formally...
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Learning Classifier Systems: A Reinforcement Learning Perspective
Reinforcement learning is defined as the problem of an agent that learns to perform a certain task through trial and error interactions with an...
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Maximization of Combustion Efficiency: A Data Mining Approach
Maximizing combustion efficiency with minimizing emissions is of importance to electric power industry. In this research, the impact of data...
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Supporting Deep Learning in an Open-ended Domain
Self-explanation has been used successfully in teaching Mathematics and Physics to facilitate deep learning. We are interested in investigating...
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Basics of Machine Learning by Support Vector Machines
Here, we talk about the (machine) learning from empirical data (i.e., examples, samples, measurements, records, patterns or observations) by applying...
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Population Dynamics of Genetic Algorithms
The theory of evolutionary algorithms has developed significantly in the last few years.A variety of techniques and perspectives have been brought to...
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Learning Classifier System with Convergence and Generalization
Learning Classifier Systems (LCSs) are rule-based systems whose rules are named classifiers. The original LCS was introduced by Holland [1, 2], and...
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Foundations of Learning Classifier Systems: An Introduction
[Learning] Classifier systems are a kind of rule-based system with general mechanisms for processing rules in parallel, for adaptive...
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Approximating Value Functions in Classifier Systems
While there has been some attention given recently to the issues of function approximation using learning classifier systems (e.g. [13, 3]), few...
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An Intrusion Detection System on The Internet of Things Using Deep Learning and Multi-objective Enhanced Gorilla Troops Optimizer
In recent years, developed Intrusion Detection Systems (IDSs) perform a vital function in improving security and anomaly detection. The effectiveness...
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Hybrid Computational Intelligence Systems for Real World Applications
This chapter covers two topics. An introduction into the field of the main disciplines used in computational intelligence and detailed description of...
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Autonomous Mobile Robots – From Science Fiction to Reality
For hundreds of years, people have dreamt of automatons that assist them in simple as well as difficult tasks. The term “automaton” dates back as far...
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Computational Complexity of the XCS Classifier System
Learning classifier systems (LCSs) are online-generalizing rule-based learning systems that use evolutionary computation techniques to evolve an...
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Two Simple Learning Classifier Systems
Since its introduction Holland’s Learning Classifier System (LCS) [Holland, 1976] has inspired much research into ‘genetics-based’ machine learning...
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A Mathematical Framework for Studying Learning in Classifier Systems
Massively parallel, rule-based systems offer both a practical and a theoretical tool for understanding systems that act usefully in complex...