INTERPLAY
INTERRELATIONSHIP BETWEEN PROBLEMS, DATA, AND ALGORITHMS.
(STG)
Data
European and global society, industry, and economy generate large volumes of data which is getting
more complex and harder to analyze
◦ Smart*, Industry 4.0, *omics
◦ Phenomena (problem) -> Observation -> Data -> Knowledge?, Value?
The ability to process and analyze data efficiently has been identified as a research goal of critical
importance
◦ EC memo ’Making the most of the Data-Driven Economy’, communication ’Towards a thriving data-driven
economy’
◦ report ’Big Data: Seizing Opportunities, Preserving Values’ by Executive Office of the President of the USA
Different types of data have different fundamental properties, pose different challenges
◦ Big vs. Deep vs. Smart
Algorithms
Traditional data processing methods struggle to keep up with the data explosion
◦ Volume, dimensionality, …
Approximate methods are in many cases a viable alternative to exact algorithms
◦ Provide a sufficiently good problem solutions in a reasonable time
Computational Intelligence (CI) includes a number of well-performing metaheuristic methods
◦ Define different high-level problem solving strategies, i.e. a search through a problem/solution space
A CI method explores the solution/problem space of an investigated problem
◦ The selection of an appropriate CI method is unknown and left to experiments
◦ There is no universal search/optimization algorithm, No Free Lunch Theorem (Wolpert, Macready)
A CI-based search for a problem solution is an interplay between the problem/data and search strategy
Data vs. Algorithms
Grand question
◦ How to chose an efficient algorithm for certain types of data, how to improve its ability to search a
particular data space
◦ CI panel at SSCI’15
Better understanding of data
◦ Domain-agnostic data fingerprinting (information-theoretic, algebraic, network/graph-based, geometric,
fractal)
A novel look at the interplay between data and (certain) algorithms per-se
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Data/solution space as a thermodynamic environment
CI methods as open dissipative dynamical systems (interacting with the environment)
Metaheuristic search as a sequence of system states between equilibria and chaos
Control of such system
PI and Vision
In the twilight zone between soft computing / optimization / data mining in the past couple of
years
◦ Work on projects dealing with many aspects of unconventional computing and algorithms
In contact with a number of leading research groups in relevant fields
◦ Postdoctoral stay in FACIA Lab (UofA, P. Musilek, environmental informatics, AIS)
◦ Pending invitations to NEO Lab (MalagaU, E. Alba, parallel metaheuristics), CIRG Group (PretoriaU, A.
Engelbrecht, PSO)
◦ Collaboration underway with UofMaribor (A. Zamuda, DE)
The ERC funding will provide a foundation to conduct a research spearheading a brand new look
on data and algorithms
◦ Bridge the gap between data and algorithms
◦ Interest in implementation/adoption of the proposed concepts already expressed