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Introduction to Computational Intelligent
The document is an introduction to Computational Intelligence (CI) presented by Ismael A. Ali at Kent State University. It covers the definition of CI, its basic properties, main paradigms, and various applications, emphasizing nature-inspired methodologies for solving complex problems. The document also outlines the interdisciplinary nature of CI and encourages exploration and development of personal algorithms based on natural processes.
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Introduction to Computational Intelligent
- 1. An Introduction to ComputationalIntelligent (CI) Ismael A. Ali Doctoral Seminar | Department of Computer Science Kent State University | Spring 2014 iali1@kent.edu
- 3. Outline Motivation Mainumbrella: Natural Computing Computational options: Levels of Abstraction Definition: CI Basic Properties of CI CI Main Paradigms Examples of Natural phenomenas Computational Intelligence: Modeling Methodology Applications of CI Recommended References
- 4. New worldof computation: Mobility; computation in everyplace Dynamic; computation for everything Adaptation and improvement; computation in every- environ Smartness: make cup of tea Uncertainty and Noise missing information Pattern recognition Needs for computation to survive: Think Adapt Sense Move
- 5. Why from nature? -The processes are well done and successfully and for years - we see the “natural processes” as “information processing systems” - We are dealing with Interdisciplinary study
- 6. Main umbrella: NaturalComputing
- 7. Do not confuse! Nature for computation: CI “Bio-computing” Computation for nature “Computational biology” Nature for engineering “Bio-inspired engineering”
- 8. Computational options: Levels ofAbstraction
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- 10. Definition Computational intelligence(CI): is a set of nature-inspired computational methodologies and approaches to address complex real-world problems to which traditional approaches, i.e., first principles modeling or explicit statistical modeling, are ineffective or infeasible wikipedi a
- 11. Computational Intelligence - Pseudonyms: NaturalComputation Nature-Inspired Computing Soft Computing Adaptive Systems
- 12. AI vs. CI CIis a specific subset of AI, but while AI focuses on the outcome, CI focuses on the mechanism. Deep Blue: highly optimized + extensive knowledge base
- 13. Basic Properties ofCI Mobility Adaptability Complexity Dynamics Robustness Sustainability And more....
- 14. CI Main Paradigms: artificial neural networks evolutionary computation fuzzy logic swarm intelligence artificial immune systems ant algorithms bee algorithms and more to come!
- 15. Examples of Naturalphenomenas Pattern recognition in different levels of abstraction
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- 20. Lets make an ComputationalIntelligence Algorithm !
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- 22. Sample Modeling Methodology Source:greensmith, DCA, PhD thesis
- 23. Applications of CI •Air Traffic Control, • Scheduling, • Machine Learning, • Pattern Recognition, • Job Shop Scheduling, • Earthquake Prediction Systems, • Market Forecasting, • Data-Mining, • User-Mining, • Resource Allocation, • Path Planning, • System modeling, • Network security
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- 26. Recommended References Conferences IEEE Computational Intelligence Society: http://cis.ieee.org/ Courses CITS7212 Computational Intelligence: The University of Western Australia http://undergraduate.csse.uwa.edu.au/units/CITS7212/schedule.html
- 27. Go out tothe nature and try made your own algorithm(s)!
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