Computational Intelligence (CI) is a sub-branch of Artificial Intelligence (AI) and is concentrated in the study of adaptive mechanisms to enable or facilitate intelligent behavior in complex and changing environments. This presentation presents the key concepts of this area and how to use Athena to create intelligent systems. Athena is a visual tool developed aiming at offering a simple approach to the development of CI-based software systems, by dragging and dropping components in a visual environment, creating a new concept, that we call CI as a Service (CIaaS).

1. Computational Intelligence: concepts
and applications using Athena
1
Pedro Almir Martins de Oliveira
pedro.oliveira@ifma.edu.br

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3. “The ability to learn/understand/deal with new situations”
“The study of how to make computers do things
at which people are doing better”(IEEE, 1996)
“[…] area of Computer Science that study techniques
to create Intelligent Systems”(Nilsson, 1998)
“Intelligent behavior involves perception,
reasoning, learning, communicating and
action in complex environments”(Nilsson, 1998)
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What is Artificial Intelligence?

4. 4
What is Artificial Intelligence?
Relationships among components of intelligent systems:

5. 1948 1956 1998 2007
“You cannot make a machine
to think for you.”
(Turing, 1948)
Hard versus soft computing
(Zadeh, 1998)
Dartmouth Artificial
Intelligence Conference
(McCarthy, 1956)
Computational Intelligence:
An Introduction
(Engelbrecht, 2007)
5

6. Computational Intelligence:
 is a sub-branch of AI and;
 is concentrated in the study of adaptive mechanisms to
enable or facilitate intelligent behavior in complex and
changing environments. (Engelbrecht, 2007).
Hard Computing versus Soft Computing:
 Traditional AI: precision and certainty;
 Soft computing exploit the tolerance for imprecision,
uncertainty and partial truth to achieve tractability,
robustness, low solution cost and better rapport with reality.
(Lotfi Zadeh, 1998)
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Concepts

7. Computational Intelligence:
 Taxonomy proposed by Engelbrecht (2007):
7
Concepts
Artificial
Neural
Networks
Evolutionary
Computation
Artificial
Immune
Systems
Swarm
Intelligence
Fuzzy
Systems

8. Artificial Neural Networks:
 Inspired in biological neural systems;
 Ability to learn, memorize and still generalize;
 Techniques:
 Perceptron, Adaline;
 Multilayer Perceptron, RBF;
 Hopfield and Kohonen Networks;
 Applications:
 Function/time series approximation;
 Control process and optimization;
 Pattern Recognition/classification;
 Clustering;
 Associative memories; 8
Concepts
Artificial
Neural
Networks

9. Evolutionary
Computation
Evolutionary Computation:
 has as its objective to mimic processes from
natural evolution;
 Genetic Algorithms, Genetic Programming,
Evolutionary Programming, Evolution Strategies and so on;
 Applications:
 Data mining;
 Combinatorial optimization;
 Fault diagnosis;
 Classification and Clustering;
 Time series approximation;
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Concepts

10. Swarm
Intelligence
Swarm Intelligence:
 originated from the study of colonies or
swarms of social organisms;
 Applications:
 Shortest path optimization;
 Graph coloring;
 Scheduling;
 Clustering;
 Techniques:
 Ant Colony Optimization;
 Particle Swarm Optimization;
 Artificial Bee Colony;
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Concepts

11. Artificial
Immune
Systems
Artificial Immune Systems:
 NIS has a great pattern matching ability, used
to distinguish between foreign cells (antigen);
 AIS models some of the aspects of a NIS;
 Techniques:
 Clonal selection;
 Danger theory;
 Network theory;
 Applications:
 Pattern recognition problems;
 Classification tasks;
 Cluster data;
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Concepts

12. Fuzzy
Systems
Fuzzy Systems:
 Inspired in human reasoning;
 Approximate reasoning;
 Techniques:
 Mamdani’s Fuzzy Inference System;
 Takagi-Sugeno-Kang FIS;
 Fuzzy C-Means (FCM);
 Applications:
 Control systems;
 Gear transmission and Braking systems;
 Controlling lifts;
 Classification and clustering;
 Function approximation; 12
Concepts

13. Applications of CI in real-world problems:
– Real-time water treatment process control with ANN (Zhang et al., 1999);
– Classification and diagnostic prediction of cancers (Khan et al., 2001);
– Hybrid approach to solve the team allocation problem (Britto et al., 2012);
– Regression testing prioritization based on FIS (Neto et al., 2012);
– Classification of social network users (Lima; Machado, 2012);
– Power system harmonics estimation (Holanda et al., 2013);
– Hydrothermal Power Systems Operation Planning (Antunes et al., 2014);
– Sentiment Classification (Anchieta et al., 2015);
– Improving the Performance of IoT Applications (Sobral et al., 2015);
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Applications

14. Another applications of CI in real-world problems:
– Robotic;
– Natural Language Processing;
– Facial and speech recognition;
– Game playing;
– Healthcare;
– Finance & Banking;
– Machine Learning;
– Military Equipment;
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Applications

15. Computational Intelligence Tools:
– When a researcher needs to use CI techniques, it is necessary to
implement them and adapt them to the specific problem;
– Programming languages: Java, Python, C++;
– Frameworks/Tools/APIs:
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Implementation

16. 16

17. High Development Cost
Difficult to reuse
Error Prone Implementations
Inappropriate Tools
Hybrid Systems
Difficult to Perform Experiments
Integration with others Systems
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20. Computational
Intelligence
+ =Cloud Computing CIaaS
Computational Intelligence
as a Service (CIaaS)
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Athena
http://athenasystems.com.br

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Future of CI
Advancements in the technologies used in CI:
– Hybrid systems;
– New techniques/algorithms;
New applications and uses of CI:
– Internet of Things (IoT);
– Ubiquitous and pervasive computing;
– And others…
– Join us! Use Athena to create Intelligent Systems;

23. Books:
– Computational Intelligence: An Introduction
• Andries Engelbrecht;
– Computational Intelligence: Principles, Techniques and Applications
• Amit Konar;
– Computational Intelligence: Concepts to Implementations
• Russell Eberhart;
– Intelligent Systems for Engineers and Scientists
• Adrian Hopgood;
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References

24. Image source:
 Image 1: http://www.gazeta-shqip.com/lajme/2015/12/24/shkencetaret-
zbulojne-gjenet-e-inteligjences-ne-tru/
 Image 2: http://www.teknikfreak.se/tekniknyheter/44495/Tekniken
_har_lart_sig_att_uppfatta_manniskors_kanslor_och_ansiktsuttryck.aspx
 Image 3: http://www.muycomputer.com/2016/02/15/robots-impacto-social
 Image 4: http://queenstownholidays.com/gallery/
 Image 5: http://www.traveltop.net/maid-of-the-mist-vii-niagara-falls-
ontario-canada/
 Image 6: http://www.lagoinha.com/ibl-vida-crista/uma-boa-ideia/
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References

25. Computational Intelligence: concepts
and applications using Athena
25
Pedro Almir Martins de Oliveira
pedro.oliveira@ifma.edu.br
http://athenasystems.com.br