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Hybrid intelligent system

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Hybrid intelligent system denotes a software system which employs, in parallel, a combination of methods and techniques from artificial intelligence subfields, such as:

Neuro-symbolic systems
Neuro-fuzzy systems
Hybrid connectionist-symbolic models
Fuzzyexpert systems
Connectionist expert systems
Evolutionary neural networks
Genetic fuzzy systems
Rough fuzzy hybridization
Reinforcement learning with fuzzy, neural, or evolutionary methods as well as symbolic reasoning methods.

From thecognitive 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 ofA.I. Systems Integration. Based on notions that there have already been created simple and specificAI systems (such as systems forcomputer vision,speech synthesis, etc., or software that employs some of the models mentioned above) and now is the time for integration to create broadAI systems. Proponents of this approach are researchers such asMarvin Minsky,Ron Sun,Aaron Sloman,Angelo Dalli andMichael A. Arbib.

An example hybrid is ahierarchical 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 performingplanning.

Intelligent systems usually rely on hybrid reasoning processes, which includeinduction,deduction,abduction and reasoning byanalogy.