Fuzzy Logic - Introduction - UFRJ

@2001 Adriano Cruz
NCE e IM - UFRJ
No. 16
Neurons
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 17
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 18
Structure
Inputs Input Weight Hidden Weight Output Outputs layer Matrix 1 layer Matrix 2 layer
ES are global search and optimization algorithms modelled from natural genetic principles such as natural selection.
They are stochastic searching methods.
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 15
ANNs
ANNs are able to learn from examples. Function approximators. Solutions not always correct. ANNs are able to generalize the acquired knowledge.
Hopefully the ANN will be able to give the
correct answer even to inputs that were not
trained.
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 20
ComputationaCruz
NCE e IM - UFRJ
No. 19
Training
Weight values change during the training process
Values are presented at the inputs and outputs are compared to the desired values.
No. 10
Fuzzy Logic
Logic that deals mathematically with imprecise information usually employed by humans. Multi-valued logic that extends Boolean logic usually employed in computer science.
Adriano Cruz NCE-IM UFRJ adriano@ufrj.br
Light travels faster than sound. That is the reason why some people look brighter until they start talking.
Linux Journal
AI emphasizes symbolic processing Acts on higher levels of intelligence AI seeks to understand
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 7
Computational Intelligence
The Metaphor
The metaphor that lays behind GAs is the natural selection. The problem of each species in the nature is seek for the best adaptations in order to survive in a hostile environment that is in constant modification.
Slides and notes: http://equipe.nce.ufrj.br/adriano/fuzzy/bibliogr-ic.htm
C. von Altrock, “Fuzzy Logic & NeuroFuzzy Applications Explained”, Prentice Hall PTR, 1995
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 14
Artificial Neural Networks
Computational models that try to emulate the structure of the human brain wishing to reproduce at least some of its flexibility and power. ANN consist of many simple computing elements – usually simple nonlinear summing operations – highly connected by links of varying strength.
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 3
Bibliography 2
H. T. Nguyen, E. A. Walker, “A First Course in Fuzzy Logic”, Chapman & Hall/CRC, 2000
Bart Kosko, “Fuzzy Thinking”, Harper Collins Publishers, 1994, ISBN 0-00-654713-3
Good solutions will survive and be combined by the natural selection process.
At the end the most fit will survive.
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 22
No. 8
Computational Intelligence
Fuzzy Logic Artificial Neural Networks Evolutionary Systems Swarm Intelligence Hybrid Systems
@2001 Adriano Cruz
NCE e IM - UFRJ
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 12
Fuzzy Logic
Who is greater than 1.80 m? Who is tall? Who weighs more than 100 kg? Who is heavy? The driver was heavy and tall.
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 13
Computational Intelligence
Fuzzy Logic Artificial Neural Networks Evolutionary Systems Swarm Intelligence Hybrid Systems
Wrong outputs cause weights to change in order to reduce the error
Process is repeated with different inputs till the ANN is able to give the correct answers
Acts on lower levels of Intelligence Uses learning extensively Pattern recognition and heuristics play important roles
@2001 Adriano Cruz
NCE e IM - UFRJ
L. H. Tsoukalas, R. E. Uhig, “Fuzzy and Neural Approaches in Engineering”, John Wiley and Sons, Inc, 1997
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 4
Summary
Introduction Fuzzy Sets Fuzzy Set Operations Fuzzy Systems
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 5
Artificial Intelligence?
“AI is the activity of providing such machines as computers with the ability to display behaviours that would be regarded as intelligent if it were observed in humans” (R. McLeod)
No. 9
Computational Intelligence
Fuzzy Logic Artificial Neural Networks Evolutionary Systems Swarm Intelligence Hybrid Systems
@2001 Adriano Cruz
NCE e IM - UFRJ
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 11
Fuzzy Logic
Used to alleviate difficulties in developing and analysing complex control systems. Function approximator Decision systems
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 23
Adaptation
The sets of characteristics of an individual, that distinguishes from everybody else, defines its survival capacity.
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 2
Bibliography 1
J. Yen, R. Langari, “Fuzzy Logic: Intelligence, Control and Information”, Prentice Hall, 1999
J. R. Jang, C. Sun, E. Mizutani, “Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, Prentice Hall, 1997
Fuzzy Logic Artificial Neural Networks Evolutionary Systems Swarm Intelligence Hybrid Systems
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 21
Evolutionary Systems
Fuzzy Logic - Introduction
Adriano Cruz NCE e IM/UFRJ Adriano@nce.ufrj.br
Computers are useless, they can only give you answers.
Pablo Picasso
2021/8/6
Introduction
“AI is the study of agents that exist in an environment, perceive and act.” (S. Russel and P. Norvig)
@2001 Adriano Cruz
NCE e IM - UFRJ
No. 6
Artificial Intelligence?