This book discusses several approaches to obtaining knowledge concerning the performance of machine learning and data mining algorithms. It shows how this knowledge can be reused to select, combine, compose and adapt both algorithms and models.
This volume offers a scientific approach to manage inter-country conflict. Readers will find that through simultaneous control of four specific aspects (democracy, dependency, allies and capacity), predicted dispute outcomes can be avoided.
This book covers the design, application and evaluation of computational models of motivation in reinforcement learning. The performance of these models is demonstrated by applications in simulated game scenarios and a live, open-ended, virtual world.
This book covers clustering using multiobjective genetic algorithms, with extensive real-life application in data mining and bioinformatics. The authors offer instructions for relevant techniques, and demonstrate real-world applications in several disciplines.
This book covers the theory and practice of multiparadigm constraint programming languages. It details the merging of programming concepts which yields multiparadigm (constraint) programming languages and examines two concrete approaches.
This text covers a field of research involving the use of neural network techniques for image recognition to tasks in the area of micromechanics. It includes theoretical analysis, details of machine tool prototypes, and results from various experiments.