Computational Intelligence

1. Computational Intelligence Rahul Kala, Department of Information Technology Indian Institute of Information Technology and Management Gwalior http://students.iiitm.ac.in/~ipg_200545/ rahulkalaiiitm@yahoo.co.in, rkala@students.iiitm.ac.in

2. Intelligence Intelligence means intellect, understanding. Intellect is a faculty or reasoning, knowledge, and thinking (Source, Oxford Dictionary) Intelligence is the computational part of the ability to achieve goals in the world. Varying kinds and degrees of intelligence occur in people, many animals and some machines. (Source, McCarthy, J. 2007, What is artificial intelligence? www-formal.stanford.edu/jmc/whatisai/whatisai.html) Artificial Intelligence: the art of making computers that behave like the ones in movies -Bill Bulko

3. Expert Systems Expert Systems are knowledge-based systems that provide expertise, similar to that of experts in a restricted application area. (Source, Kasabov, Nikola K. 1998, Foundations of Neural Networks, Fuzzy Systems and Knowledge Engineering, MIT Press).

4. Machine Learning Machine learning refers to the methods are computer methods for accumulating, changing, and updating knowledge in an AI computer system. (Source: Kasabov, Nikola K. 1998, Foundations of Neural Networks, Fuzzy Systems and Knowledge Engineering, 2nd Edition, MIT Press) • Forming Rules • Knowledge from data • Reproducibility • Generalization

5. Applications

6. Soft Computing

7. Artificial Neural Network The neural network, by its simulating a biological neural network, is a novel computer architecture and a novel algorithmization architecture relative to conventional computers. It allows using very simple computational operations (additions, multiplication and fundamental logic elements) to solve complex, mathematically ill-defined problems, nonlinear problems or stochastic problems. (Source: Graupe, Daniel, 2007, Principles of Artificial Neural Networks, 2nd Edition, World Scientific). • Motivation from Human Brain • Functional Predictors • Classifiers • Training and Testing Data

8. Fuzzy Inference Systems • Derived from Aristotle’s Boolean Logic • Degree of certainty • Rule Based Approach Fuzzy Inference Systems are systems formulating the mapping from a given input to an output using fuzzy logic (Source, MATLAB Guide).

9. Evolutionary Algorithms Evolutionary Algorithms are algorithms that maintain a population of structures that evolve according to the rules of selection and other operators, such as recombination and mutation. Each individual in the population is evaluated, receiving a measure of its fitness in the environment (Source, Spears, William M. 2000, Evolutionary Algorithms, Springer) • Motivation from Natural Evolution process • Darwin's Survival of the Fittest • Optimizing Agents

10. Nature and Biological inspiration

11. Input Preprocessing Feature Extraction Pattern Matching Output Historical Database Recognition Systems Constraints • Dimensionality • Processing Power • Data Set Size

12. Biometrics

13. Distance between centre points of eyes Centre point of left eye Centre point of right eye Width of left eye Width of right eye Length of left eye Length of right eye Distance between centre points of eyes and mouth Width of mouth Centre point of mouth Length of mouth Biometrics

14. Robotics • Humanoid • Assistive • Swarm Behavior • Medical Rehabilitation • Space • UAVs • Nano Operations

15. Growing Areas

16. Into the Future

17. Thank You