science

Hybrid intelligent system

Hybrid intelligent system is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Hybrid intelligent system rather than just read about it. In short: 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…

Key takeaways

Hybrid intelligent system belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Hybrid intelligent system to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Hybrid intelligent system from memory before moving on to harder problems.

Reference excerpt

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, Angelo Dalli 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 (even by hybrid wisdom). Intelligent systems usually rely on hybrid reasoning processes, which include induction, deduction, abduction and reasoning by analogy.

See also AI alignment AI effect Applications of artificial intelligence Artificial intelligence systems integration Intelligent control Lists List of emerging technologies Outline of artificial intelligence

References

R. Sun & 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. Ibaraki, S. Hybrid Intelligence interview with Angelo Dalli in IEEE Technology and Management Society. 2024. 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 & 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.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

Worked examples

Example 1 — a first encounter with Hybrid intelligent system

Start with the simplest possible case. Write down what Hybrid intelligent system claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Hybrid intelligent system before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Hybrid intelligent system ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Hybrid intelligent system

In research: Hybrid intelligent system appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Hybrid intelligent system in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Hybrid intelligent system is common in secondary-school and first-year university syllabi. It links to neighbouring topics Artificial intelligence, so understanding it makes those chapters shorter.
In everyday life: Look for Hybrid intelligent system outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Hybrid intelligent system in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Hybrid intelligent system means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Hybrid intelligent system out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Hybrid intelligent system in simple terms?

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…

Why does Hybrid intelligent system matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Hybrid intelligent system?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Hybrid intelligent system.