Petr Dostál

Petr Dostál

Economy & Management – Decision Making – Artificial Intelligence

Artificial Intelligence - Soft Computing - Fuzzy logic - Genetic algorithms - Neural networks - Chaos Theory

About me
Curriculum vitae
CV in Czech
Contact details

My books
Classic methods
Fuzzy logic
Neural network
Genetic algorithms
Hybrid methods
Chaos theory

BUT Brno, Czechia
MUNI Brno, Czechia
TBU Zlin, Czechia
EPI Kunovice, Czechia
SUA Nitra, Slovakia
NTU Nottingham, UK  
ASU Cairo, Egypt
DOM Chicago, USA
UCH Chicago, USA
KU Kathmandu, Nepal
AU Ariel, Izrael
NCCU Taipei, Taiwan
HIT Haldia, Indie
UAS Leiden, Netherlands
SIU Győr, Hungary
UD Dubai, UAE

PhD students
Foreign students


About Soft computing
My hobbies
My organ songs

What Is Soft Computing?

A Definition of Soft Computing - adapted from L.A. Zadeh

Soft computing differs from conventional (hard) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation. In effect, the role model for soft computing is the human mind. The guiding principle of soft computing is: Exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low solution cost. The basic ideas underlying soft computing in its current incarnation have links to many earlier influences, among them Zadeh's 1965 paper on fuzzy sets; the 1973 paper on the analysis of complex systems and decision processes; and the 1979 report (1981 paper) on possibility theory and soft data analysis. The inclusion of neural computing and genetic computing in soft computing came at a later point.

At this juncture, the principal constituents of Soft Computing (SC) are Fuzzy Logic (FL), Neural Computing (NC), Evolutionary Computation (EC) Machine Learning (ML) and Probabilistic Reasoning (PR), with the latter subsuming belief networks, chaos theory and parts of learning theory. What is important to note is that soft computing is not a melange. Rather, it is a partnership in which each of the partners contributes a distinct methodology for addressing problems in its domain. In this perspective, the principal constituent methodologies in SC are complementary rather than competitive. Furthermore, soft computing may be viewed as a foundation component for the emerging field of conceptual intelligence.

Soft Computing Applications

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