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 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 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 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 book covers general logical tools for handling change. The tools are preferential reasoning, theory revision and reasoning in inheritance systems. Logics examined are nonmonotonic, deontic, modal, intuitionistic and temporal as well as counterfactuals.
The first textbook ever to cover multi-relational data mining and inductive logic programming, this book fully explores logical and relational learning. Ideal for graduate students and researchers, it also looks at statistical relational learning.
This book presents an overview of the field of language technology for cultural heritage and its associated academic research. It covers applications ranging from pre-processing and data cleaning to the adaptation and compilation of linguistic resources.