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.
hybrid, intelligent, system, denotes, software, system, which, employs, parallel, combination, methods, techniques, from, artificial, intelligence, subfields, such, neuro, symbolic, systems, neuro, fuzzy, systems, hybrid, connectionist, symbolic, models, fuzzy. 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 Fuzzy expert 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 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 Intelligent systems usually rely on hybrid reasoning processes which include induction deduction abduction and reasoning by analogy See also EditAI alignment AI effect Applications of artificial intelligence Artificial intelligence systems integration Intelligent controlListsList of emerging technologies Outline of artificial intelligenceNotes EditReferences EditR Sun amp L Bookman eds Computational Architectures Integrating Neural and Symbolic Processes Kluwer Academic Publishers Needham MA 1994 http www cogsci rpi edu rsun book2 ann html Archived 2009 05 05 at the Wayback Machine S Wermter and R Sun eds Hybrid Neural Systems Springer Verlag Heidelberg 2000 http www cogsci rpi edu rsun book4 ann html Archived 2009 09 24 at the Wayback Machine R Sun and F Alexandre eds Connectionist Symbolic Integration Lawrence Erlbaum Associates Mahwah NJ 1997 Albus J S Bostelman R Chang T Hong T Shackleford W and Shneier M Learning in a Hierarchical Control System 4D RCS in the DARPA LAGR Program NIST 2006 A S d Avila Garcez Luis C Lamb amp Dov M Gabbay Neural Symbolic Cognitive Reasoning Cognitive Technologies Springer 2009 ISBN 978 3 540 73245 7 International Journal of Hybrid Intelligent Systems http www softcomputing net ijhis http www iospress nl html 14485869 php Archived 2005 12 11 at the Wayback Machine International Conference on Hybrid Intelligent Systems http his hybridsystem com HIS 01 http www softcomputing net his01 HIS 02 https web archive org web 20060209160923 http tamarugo cec uchile cl his02 HIS 03 http www softcomputing net his03 HIS 04 https web archive org web 20060303051902 http www cs nmt edu his04 HIS 05 https web archive org web 20051223013031 http www ica ele puc rio br his05 HIS 06 https web archive org web 20110510025133 http his ncei06 kedri info HIS 7 September 17 19 2007 Kaiserslautern Germany http www eit uni kl de koenig HIS07 Web his07main html hybrid systems resources http www cogsci rpi edu rsun hybrid resource html Archived 2009 09 25 at the Wayback Machine Retrieved from https en wikipedia org w index php title Hybrid intelligent system amp oldid 1178379095, wikipedia, wiki, book, books, library,
