The document discusses the past, present, and future of natural computing. It describes how the field has traditionally focused on designing nature-inspired algorithms and synthesizing natural phenomena [1]. However, the document argues the field needs to advance in a more formal and consistent way by addressing three grand challenges: transforming natural computing into a transdisciplinary discipline, unveiling information processing in natural systems, and engineering natural computing systems [2]. Addressing these challenges could help the field move beyond designing similar algorithms and better understand computation in nature [3].

1. The Grand Challenges in
Natural Computing Research
Leandro Nunes de Castro
Lnunes@mackenzie.br
@lndecastro
Computing and Informatics Faculty &
Graduate Program in Electrical Engineering
Natural Computing Laboratory (LCoN)
www.mackenzie.br/lcon.html
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BRACIS 2012: Brazilian Conference on Intelligent Systems, Curitiba, Brazil, October, 2012

2. Natural Computing
An Overview*
* de Castro, L. N. (2007), “Fundamentals of Natural Computing: An Overview”, Physics of Life Reviews, 4(1), pp. 1-36.
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3. Computing:
Yesterday, Today and Tomorrow*
• 1940s: Study of automatic computing;
• 1950s: Study of information processing;
• 1960s: Study of phenomena surrounding
computers;
• 1970s: Study of what can be automated;
• 1980s: Study of computation;
• 2000s: Study of information processes, both
natural and artificial.
* Denning, P. (2008), “Computing Field: Structure”, In B. Wah (Ed.), Wiley Encyclopedia of Computer Science and
Engineering, Wiley Interscience.
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4. From the early days of computer
science, by the 1940s, researchers
have been interested in tracing
parallels and designing
computational models and
abstractions of natural phenomena.
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11. Natural Computing: The Old View
Bioinspiration
Theoretical
Works
Mathematical Natural Computational
Synthesis of Natural
Models
Computing Phenomena
Empirical
Works Computing with
Natural Materials

12. Natural Computing: The New Perspective
Computer Natural
Modeling of
Nature computing is a
science
concerned with
the
Computing
Natural Nature- investigation
with New Inspired
Materials Computing Computing and design of
information
processing in
natural and
Computer computational
Synthesis of
Natural systems.
Phenomena

13. Natural Computing
The Grand Challenges*
* de Castro, L. N.; Xavier, R. S.; Pasti, R.; Maia, R. D.; Szabo, A.; Ferrari, D. G. (2012), "The Grand Challenges in Natural
Computing Research: The Quest for a New Science", Int. J. Nat. Comp. Res., 2(4), p. 16.
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14. The Grand Challenges (GCs)
The GCs aim at defining research questions that
tend to be important in the long
term, identifying and characterizing potential
grand research problems. These may allow the
formulation of projects capable of producing
major scientific advancements, with practical
applications for society and technology.
Emphasis is in advancing science, a vision
beyond specific projects, a clear and objective
success evaluation and a great ambition.*
* www.sbc.org.br
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15. Biology Multidisciplinarity
Computer Natural
Physics
Science Computing
Biology
Chemistry
Computer Natural Physics
Science Computing
Interdisciplinarity
Chemistry
15

16. How to transpose Natural
Computing into a
Biology transdisciplinary context?
Computer Natural Physics
Science Computing
Chemistry
GC 1: Transforming Natural Computing into
a transdisciplinary discipline 16

17. “Computer science differs from
physics in that it is not actually a
science. It does not study natural
objects. Neither is it mathematics. It’s
like engineering – about getting to do
something, rather than dealing with
abstractions”.*
“Biology is today an information
science”**
* Feynman, R. P. (1996), “The Feynman Lectures on Computation”, In A. J. G. Hey and R. W. Allen (Ed.), (Reading, MA:
Addison-Wesley).
** Denning, P. J., (2001) (Ed.), The Invisible Future: The Seamless Integration of Technology in Everyday Life, McGraw-
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Hill.

18. What is the Natural Computing role in this
Informational Natural Sciences Era?
Overcoming this challenge will bring two
important benefits to Computing and Nature:
• A Rethinking (and probably Redesign) of
Computing
• A New Form of Interacting With and Using
Nature
GC 2: Unveiling and harnessing
information processing in natural systems
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19. Natural systems are open systems that
communicate with the environment
presenting a complex and emergent
behavior. Complex biological systems must
be modeled as self-referential, self-
organizing, and auto-generative systems
whose computational behavior goes far
beyond the TM/VN paradigm. The system
restructures itself in a hardware-software
non-dissociable interaction: the hardware
defines the software, and the software
defines the hardware. 19

20. Are there standards to design natural
computing systems?* To what degree defining
standards for the engineering of Natural
Computing systems is a limiting factor for the
creative development of the field?
GC 3: Engineering Natural Computing Systems.
* Brueckner, S. A.; Serugendo, G. D. M.; Karageorgos, A.; Nagpal, R., (2005), Engineering Self-Organizing
Systems, Lecture Notes in Artificial Intelligence, 3464, Springer.
* de Castro, L. N. (2001), Immune Engineering: Development and Application of Computational Tools Inspired by
Artificial Immune Systems, Ph. D. Thesis presented at the Computer and Electrical Engineering
School, Unicamp, Brazil.
* Fernandez-Marquez, J. L.; Serugendo, G. D. M.; Montagna, S.; Viroli M.; Arcos J. L (2012), “Description and
Composition of Bio-Inspired Design Patterns: A Complete Overview”, Natural Computing, Online, DOI
10.1007/s11047-012-9324-y.
* Nagpal, R.; Mamei, M. (2004), “Engineering Amorphous Computing Systems”, Multiagent Systems, Artificial
Societies, and Simulated Organizations, 11, Part V, pp. 303-320. 20

21. The Grand Challenges in
Natural Computing Research
• The field needs to advance in a more
consistent and formal way.
• Transforming Natural Computing into a
Transdisciplinary Discipline.
• Unveiling and Harnessing Information
Processing in Natural Systems.
• Engineering Natural Computing Systems.
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22. Discussion
Natural Computing:
The Past, Present and Future
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23. The Past and Present
• Focus on:
– Designing novel nature-inspired algorithms.
– Synthesizing natural phenomena.
– Using natural materials for computing.
• Real-world applications are
unquestionable, but the field seems to be
stuck on the same types of algorithms.
• Researchers are taking efforts to look at and
formalize information processing in natural
and computational systems.*
* Zenil, H. (2012) (Ed.), A Computable Universe: Understanding Computation & Exploring Nature as
Computation, World Scientific.
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24. And the Future?
• Grand Challenges for the field:
– Transforming Natural Computing into a
Transdisciplinary Discipline.
– Unveiling and Harnessing Information Processing
in Natural Systems.
– Engineering Natural Computing Systems.
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25. Thank You!
Questions? Comments?
Leandro Nunes de Castro
Lnunes@mackenzie.br
http://slideshare.net/lndecastro
@lndecastro
www.mackenzie.br/lcon.html
www.computacaonatural.com.br
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