Abstract:
Many complex problems including financial investtnent planning. foreign exchange
trading, knowledge discovery from large/multiple databases 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 because they have a large number of parts or components that
have many interactions. On the other hand, agents offer a new and often more appropriate
route to the development of complex systems, especially in open and dynamic
environments. In this paper, it is argued that agent technology is well suited for constructing
hybrid intelligent systems (especially loosely coupled hybrid intelligent systems)
through a successful case study. A great number of heterogeneous computing
techniques/packages are easily integrated into the experimental system under a unifying
agent framework, which implies that agent technology can greatly facilitate the
construction of hybrid intelligent systems.
