TY  - BOOK
AU  - Zhang,Zili
AU  - Zhang,Chengqi
ED  - SpringerLink (Online service)
TI  - Agent-Based Hybrid Intelligent Systems: An Agent-Based Framework for Complex Problem Solving 
T2  - Lecture Notes in Computer Science,
SN  - 9783540246237
AV  - Q334-342 
U1  - 006.3 23
PY  - 2004///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg
KW  - Computer science
KW  - Software engineering
KW  - Database management
KW  - Artificial intelligence
KW  - Information systems
KW  - Computer Science
KW  - Artificial Intelligence (incl. Robotics)
KW  - Software Engineering
KW  - Computation by Abstract Devices
KW  - Database Management
KW  - Computer Appl. in Administrative Data Processing
N1  - Fundamentals of Hybrid Intelligent Systems and Agents -- 1 Introduction -- 2 Basics of Hybrid Intelligent Systems -- 3 Basics of Agents and Multi-agent Systems -- Methodology and Framework -- 4 Agent-Oriented Methodologies -- 5 Agent-Based Framework for Hybrid Intelligent Systems -- 6 Matchmaking in Middle Agents -- Application Systems -- 7 Agent-Based Hybrid Intelligent System for Financial Investment Planning -- 8 Agent-Based Hybrid Intelligent System for Data Mining -- Concluding Remarks -- 9 The Less the More -- Appendix: Sample Source Codes of the Agent-Based Financial Planning System -- References
N2  - Solving complex problems in real-world contexts, such as financial investment planning or mining large data collections, involves many different sub-tasks, each of which requires different techniques. To deal with such problems, a great diversity of intelligent techniques are available, including traditional techniques like expert systems approaches and soft computing techniques like fuzzy logic, neural networks, or genetic algorithms. These techniques are complementary approaches to intelligent information processing rather than competing ones, and thus better results in problem solving are achieved when these techniques are combined in hybrid intelligent systems. Multi-Agent Systems are ideally suited to model the manifold interactions among the many different components of hybrid intelligent systems. This book introduces agent-based hybrid intelligent systems and presents a framework and methodology allowing for the development of such systems for real-world applications. The authors focus on applications in financial investment planning and data mining
UR  - http://dx.doi.org/10.1007/b95170
ER  -