Hybrid intelligent system denotes a software system which employs, in parallel, a combination of methods and techniques from artificial intelligence subfields, such as:
Reinforcement learning with fuzzy, neural, or evolutionary methods as well as symbolic reasoning methods.
From the
cognitive science perspective, every natural intelligent system is hybrid because it performs mental operations on both the symbolic and subsymbolic levels. For the past few years, there has been an increasing discussion of the importance of
A.I. Systems Integration. Based on notions that there have already been created simple and specific
AI systems (such as systems for
computer vision,
speech synthesis, etc., or software that employs some of the models mentioned above) and now is the time for integration to create broad
AI systems. Proponents of this approach are researchers such as
Marvin Minsky,
Ron Sun,
Aaron Sloman, and
Michael A. Arbib.
An example hybrid is a
hierarchical control system in which the lowest, reactive layers are sub-symbolic. The higher layers, having relaxed time constraints, are capable of reasoning from an abstract world model and performing
planning.