neural networks and fuzzy systems - engenharia … · summary 1 - introduction – connectionist...
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Soft Computing
Neural Networks and Fuzzy Systems
Prof. Dr.-Ing. Adolfo BauchspiessUniversidade de Brasília - Brazil
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic
Summary
1 - Introduction – Connectionist Intelligent Systems2 - Artificial Neural Networks3 - Fuzzy Logic and Fuzzy Systems4 - Examples and Applications5 - Conclusions
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic
5 - Conclusions
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Part 1
Introduction – Connectionist Intelligent Systems
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic 3
Some publications - Intelligent Systems
� Internacional Journals
� Neural Networks, IEEE Transaction son
� Fuzzy Systems, IEEE Transactions on
� Intelligent Systems Engineering
� Intelligent Systems, IEEE
�IntelligentTransportationSystems, IEEE Transactionson
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic
�IntelligentTransportationSystems, IEEE Transactionson.....
� Conferences
.....
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Epistemology –“Philosophy of Knowledge”
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic 5
Heuristics
D Domain
Optimal Solution
D
S
H1H2
H3SolutionSpace
Heuristics give sub-optimal solutions.
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic
Heuristics
Solution SpaceS
A heuristic rule leads from the domain space to the solution spaceD
S
H2
H3 Optimal SolutionSolution Space
H4H5H1
“Well-formed” Heuristics are close to the optimal solution.
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Dislexy?
I cnduo't bvleiee taht I culod aulaclty uesdtannrd waht I wasrdnaieg. Unisg the icndeblire pweor of the hmuan mnid, aocdcrnig to rseecrahat Cmabrigde Uinervtisy, it dseno'tmttaer
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic
aocdcrnig to rseecrahat Cmabrigde Uinervtisy, it dseno'tmttaerin waht oderr the lterets in a wrod are, the olny irpoamtnt tihngis taht the frsit and lsat ltteer be in the rhgit pclae. The rset canbe a taotl mses and you can sitll raed it whoutit a pboerlm. Tihs isbucseae the huamn mnid deos not raed ervey ltteer by istlef, butthe wrod as a wlohe. Aaznmig, huh? Yaeh and I awlyas tghhuotslelinpg was ipmorantt! See if yuor fdreins can raed tihs too.
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Giant x 3D Ilusion?
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic 8
Waves?
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic 9
Simpathic?
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Antipathic?
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Introduction - Connectionist Intelligent Systems
Artificial IntelligenceScience field that studies paradigmsthat aims to explain howintelligent behaviourcan emerge
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic
can emergefrom artificial implementations, in computers.
Intelligence: learning, adaptation, comprehension
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IA Paradigms
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic
Intelligence : learning, adaptation, comprehension
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Connectionist Paradigm
Considers to be virtually impossible to transform in algorithms -i.e., to reduce to a sequence of logical and arithmetic stepsmany tasks that the human mind performs with ease and speed, for example:
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic
· Face Recognition,· Comprehend and translate natural languages,· Memory evocation by association,· Games...
for example:
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Connectionist Paradigm
The computational process have to mimicthe brain capacity of self-organization → learn!
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic 15
Symbolist versus ConectionistParadigm
-Perception
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic
The Kanizsa square, 1976
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“Local Coherency –Global Paradox"
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Sandro delPrete. Enigmas Visuais. Rio de Janeiro, 2004, p. 45
M.C.Escher
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic
“Positive Truth X Negative Truth”
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Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic
“Up stairsX
Down stairs”
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Paradigma Simbolista versus Conexionista
- J.S. Bach “Coerência Local - Paradoxo Global”
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic
Pseudo-rising scale
played on a vibraphone
Shepard's scale
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Synapses Formation
Laboratório de Automação e Robótica - A. Bauchspiess– Soft Computing - Neural Networks and Fuzzy Logic
0-2 years 2 years to puberty Adult
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Olfative Information Processing
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Auditive Information Processing
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Epilepsy Pacient –without left brain hemisphere since 12 years age
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