Abstract:
Many complex problems including financial investment planning
require hybrid intelligent systems that integrate many intelligent
techniques including expert systems, fuzzy logic, neural networks, and
genetic algorithms. However, hybrid intelligent systems are difficult to
develop due to complicated interactions and technique incompatibilities.
This paper describes a hybrid intelligent system for financial investment
planning that was built from agent points of view. This system currently
consists of 13 different agents. The experimental results show that all
agents in the system can work cooperatively to provide reasonable investment
advice. The system is very flexible and robust. The success of
the system indicates that agent technologies can significantly facilitate
the construction of hybrid intelligent systems.
