Abstraction in Artificial Intelligence and Complex SystemsAbstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences. After discussing the characterizing properties of abstraction, a formal model, the KRA model, is presented to capture them. This model makes the notion of abstraction easily applicable by means of the introduction of a set of abstraction operators and abstraction patterns, reusable across different domains and applications. It is the impact of abstraction in Artificial Intelligence, Complex Systems and Machine Learning which creates the core of the book. A general framework, based on the KRA model, is presented, and its pragmatic power is illustrated with three case studies: Model-based diagnosis, Cartographic Generalization, and learning Hierarchical Hidden Markov Models. |
Contents
2 | |
11 | |
3 Abstraction in Artificial Intelligence | 49 |
4 Definitions of Abstraction | 64 |
5 Boundaries of Abstraction | 117 |
6 The KRA Model | 141 |
7 Abstraction Operators and Design Patterns | 178 |
8 Properties of the rrr Model | 223 |
13 Conclusion | 407 |
Appendix AConcrete Art Manifesto | 413 |
Appendix BCartographic Results for Roads | 415 |
Appendix CRelational Algebra | 417 |
Appendix DBasic Notion of First Order Logics | 421 |
Appendix EAbstraction Operators | 426 |
Appendix FAbstraction Patterns | 441 |
Appendix GAbstraction of Michalskis Train Problem | 443 |
Other editions - View all
Abstraction in Artificial Intelligence and Complex Systems Lorenza Saitta,Jean-Daniel Zucker No preview available - 2013 |
Abstraction in Artificial Intelligence and Complex Systems Lorenza Saitta,Jean-Daniel Zucker No preview available - 2013 |
Abstraction in Artificial Intelligence and Complex Systems Lorenza Saitta,Jean-Daniel Zucker No preview available - 2013 |
Common terms and phrases
abstract space abstraction operators abstraction process aggregation algorithm applied approach approximation arity Artificial Intelligence associated attributes behavior building co-domain cognitive color complexity components computational concept concrete configuration space contains corresponding database defined definition denoted described description frame domain elements entities equivalence classes example FCOV feature selection formula function Giunchiglia given ground hidden hiding hierarchy infomorphism information hiding instance introduced Kolmogorov complexity KRA model language Let us consider LoAs logical Machine Learning method meth method meth[Pg Miles Smith namely nodes objects of type observations obtained P-Set patterns predicate mapping problem properties proposed query RCOV reformulation Reinforcement Learning relation relational algebra relevant reported in Fig representation represented Sect semantic simplicity solve specific Springer Science+Business Media structure subset supervised learning task theories of abstraction tion tuples values variable Waggr whereas