My scientific papers

Dissertations / theses

  1. Analysis of Quantum-Inspired Evolutionary Algorithms - PhD dissertation (in Polish)
    Abstract: This dissertation concerns Quantum-Inspired Evolutionary Algorithms (QIEAs), state-of-the-art artificial intelligence techniques, which draw inspiration from both biological evolution and unitary evolution of quantum systems. Both theoretical approaches have been applied and their empirical verification in precisely planned numerical experiments has been provided. The thesis introduces a new way of representing solutions in genetic algorithms using adjacent quantum registers and a new genetic operator working in the space of a higher dimension in quantum-mechanical sense. New notions and fundamentals of Higher-Order Quantum-Inspired Genetic Algorithms have been presented. The author’s original QIGA2 algorithm has been created on the basis of this theory.

  2. On The Evolutionary Design of Quantum Algorithms - Master’s thesis (in Polish)
    Abstract: This thesis is focused on quantum computing and its possible applications of genetic algorithms. Quantum computing is considered in the terms of quantum gates computational model. Proposal of object model for quantum computing is presented. Practical part of this thesis consists of the quantum computing library (qclib) allowing to simulate a quantum computer. The basic quantum algorithms are presented and implemented using qclib: Grover’s fast search algorithm, quantum teleportation, quantum superdense coding and production of entangled quantum states. Generation of such quantum algorithms is a difficult task for human. They are unintuitive and computationally intensive. For that reason hybrid systems combining quantum computing and genetic algorithms are considered. In this thesis simple and modified genetic algorithms are used and compared to evolve quantum gates. Complete quantum circuits are created using genetic programming. Some of possible approaches are illustrated with numerical experiments.

Journals and conference papers

The papers order below is based on my current personal assessment of these works (so it is neither chronological nor the journal points ranking).

  1. Higher-Order Quantum-Inspired Genetic Algorithms
    R.Nowotniak, J.Kucharski
    Abstract: This paper presents a theory and an empirical evaluation of Higher-Order Quantum-Inspired Genetic Algorithms. Fundamental notions of the theory have been introduced, and a novel Order-2 Quantum-Inspired Genetic Algorithm (QIGA2) has been developed. Contrary to all QIGA algorithms which represent quantum genes as independent qubits, in higher-order QIGAs quantum registers are used to represent genes strings, which allows modelling of genes relations using quantum phenomena. Performance comparison has been conducted on a benchmark of 20 deceptive combinatorial optimization problems. It has been presented that using higher quantum orders is beneficial for genetic algorithm efficiency, and the new QIGA2 algorithm outperforms the old QIGA algorithm tuned in highly compute-intensive metaoptimization process.
    Proceedings of Federated Conference on Computer Science and Information Systems, Warsaw, 2014

  2. Convergence analysis of Quantum-Inspired Evolutionary Algorithms based on Banach fixed point theorem
    R.Nowotniak, J.Kucharski
    Abstract: In this paper a convergence analysis of general Quantum-Inspired Evolutionary Algorithm based on the Banach fixed point theorem has been performed. A new quality measure for quantum genotypes has been proposed and the algorithm has been considered in the relevant metric space. Necessary conditions for the convergence of the algorithm have been discussed. Finally, the analysis has been illustrated by a Quantum-Inspired Genetic Algorithm.
    Proceedings of the 2012 FIMB PhD students conference

  3. Evolutionary Algorithms Approach for Cutting Stock Problem
    A.Romanowski, R.Nowotniak, K.Kawecki, T.Jaworski, Z.Chaniecki, K.Grudzień
    Abstract: This paper contain study of three algorithms for optimisation of use of materials for cutting process. Cutting Stock Problem (CSP) and one dimensional guillotine cat variant of the CSP is introduced. Afterwards three different way of solving the problem are presented. For each of theme one algorithm is proposed. First is creating all the possible solutions and choosing the best one. Second is trying to recreate a human thinking process by using a heuristic search. Third one is inspired by an evolution process in the nature. Design and implementation of each of them is presented. Proposed algorithms are tested and compared to each other and also to the other known solutions.
    Image Processing & Communications 17 (4), 297-306, 2012

  4. GPU-based Tuning of Quantum-Inspired Genetic Algorithm for a Combinatorial Optimization Problem
    R.Nowotniak, J. Kucharski
    Abstract: This paper concerns efficient parameters tuning (meta-optimization) of a state-of-the-art metaheuristic, Quantum-Inspired Genetic Algorithm (QIGA), in a GPU-based massively parallel computing environment (NVidia CUDATMtechnology). A novel approach to parallel implementation of the algorithm has been presented. In a block of threads, each thread transforms a separate quantum individual or different quantum gene; In each block, a separate experiment with different population is conducted. The computations have been distributed to eight GPU devices, and over 400x speedup has been gained in comparison to Intel Core i7 2.93GHz CPU. This approach allows efficient meta-optimization of the algorithm parameters. Two criteria for the meta-optimization of the rotation angles in quantum genes state space have been considered. Performance comparison has been performed on combinatorial optimization (knapsack problem), and it has been presented that the tuned algorithm is superior to Simple Genetic Algorithm and to original QIGA algorithm.
    Published in Bulletin of The Polish Academy of Sciences: TechnicalSciences,
    Vol. 60, No. 2, 2012, ISSN 0239-7528
    paper (PDF) in the Bulletin

  5. GPU-based Tuning of Quantum-Inspired Genetic Algorithm for a Combinatorial Optimization Problem
    R.Nowotniak, J. Kucharski
    Abstract: This paper concerns efficient parameters tuning (meta-optimization) of a state-of-the-art metaheuristic, Quantum-Inspired Genetic Algorithm, in a GPU-based massively parallel computing environment (NVidia CUDA™ technology). A novel approach to parallel implementation of the algorithm has been presented. The computations have been distributed to eight GPU devices, and over 400x speedup has been gained. This approach allows efficient meta-optimization of the algorithm which has been demonstrated on combinatorial optimization (knapsack problem). Published in Proceedings of the XIV International Conference SYSTEM MODELING and CONTROL JUNE 27-29, 2011, ISSN 978-83-927875-1-8 paper (PDF) in the conference proceedings presentation (PDF) from the conference

  6. Meta-optimization of Quantum-Inspired Evolutionary Algorithms in The Polish Grid Infrastructure
    R.Nowotniak
    Abstract:The presented research concerns meta-optimization of Quantum-Inspired Evolutionary Algorithms (QIEA) with the use of computational resources of The Polish Grid Infrastructure PL-GRID. In QIEA algorithms, additional elements of randomness are introduced. They are inspired by properties of quantum mechanical systems. The intensified random factors strongly influence effectiveness of the algorithms in numerical and combinatorial optimization problems. Parameters of QIEA algorithms determine the influence of the random factors. Automatic tuning of the parameters values is possible by state-of-the-art meta-optimization techniques, which involves a considerable computational cost. Published in Proceedings of the 2nd Scientific Session of TUL PhD Students, ISBN 978-83-7283-490-4 The Session was held in April 2012 in Rogow, Poland

  7. Publication patterns in the social sciences and humanities: evidence from eight European countries
    Emanuel Kulczycki, Tim CE Engels, Janne Pölönen, Kasper Bruun, Marta Dušková, Raf Guns, Robert Nowotniak, Michal Petr, Gunnar Sivertsen, Andreja Istenič Starčič, Alesia Zuccala
    Abstract: This study investigates patterns in the language and type of social sciences and humanities (SSH) publications in non-English speaking European countries to demonstrate that such patterns are related not only to discipline but also to each country’s cultural and historic heritage. We investigate publication patterns that occur across SSH publications of the whole of the SSH and of economics and business, law, and philosophy and theology publications in the Czech Republic, Denmark, Finland, Flanders (Belgium), Norway, Poland, Slovakia, and Slovenia. We use data from 74,022 peer-reviewed publications from 2014 registered in at least one of the eight countries’ national databases and for 272,376 peer-reviewed publications from the period of 2011–2014 registered in at least one of the seven countries’ national databases (for all countries except Slovakia). Our findings show that publication patterns differ both between fields (e.g. patterns in law differ from those in economics and business in the same way in Flanders and Finland) and within fields (e.g. patterns in law in the Czech Republic differ from patterns in law in Finland). We observe that the publication patterns are stable and quite similar in West European and Nordic countries, whereas in Central and Eastern European countries the publication patterns demonstrate considerable changes. Nevertheless, in all countries, the share of articles and the share of publications in English is on the rise. We conclude with recommendations for science policy and highlight that internationalization policies in non-English speaking countries should consider various starting points and cultural heritages in different countries.

  8. Publication patterns in the social sciences and humanities in Flanders and Poland
    Emanuel Kulczycki, Tim CE Engels, Robert Nowotniak
    Abstract: This paper investigates internationalization patterns in the language and type of social sciences and humanities publications in non-English speaking countries. This research aims to demonstrate that such patterns are related not only to discipline but also to each country’s cultural and historic heritage. We used data from Flemish and Polish databases collected between 2009 and 2014. In Flanders, on the one hand, we found that changes in the use of languages and publication types were moderate and occurred gradually over several years. In Poland, on the other hand, we found significant shifts in the use of certain publication types, sometimes from year to year. Examining the social sciences and humanities literature both as a whole and broken down by discipline, we observed similar variability over time in the proportion of work published in English and in article form. However, we found remarkable differences between Flanders and Poland regarding the most commonly used languages and publication types. Overall, we found few similarities between Flemish and Polish social sciences and humanities publication patterns.

  9. GPU-based massively parallel implementation of metaheuristic algorithms
    R.Nowotniak, J. Kucharski
    Abstract: In this paper, implementation of Quantum-Inspired Genetic Algorithm(QIGA) in massively parallel environment (Graphics Processing Units) has been presented. Contrary to many recent papers concerning parallel implementation of evolutionary algorithms, in this paper a novel approach has been taken. QIGA algorithm has been implemented entirely as a computational kernel. Parallelization of the algorithm has been performed on two levels: In a block of threads, each thread transforms a separate individual or different gene; In each block, separate populations with same or different parameters are evolved. Finally, the computations have been distributed to eight GPU devices, and over 400x speedup has been gained in comparison to sequential implementation of the algorithm in ANSI C on one Intel Core i7 2.93GHz CPU core. Correctness of the results has been verified in statistical analysis. The presented approach can be applied to experimentation with a broad class of metaheuristics. The Conference was held in June 2011 in Słok, Poland paper (PDF) in the conference proceedings presentation and poster from the conference

  10. Modelling Reality In Visual Python
    R.Nowotniak, C.Draus, M. Nowak, G.Rybak
    Abstract: In summer semester of the academic year 2010/2011, the course entitled “Programming in Scripting Languages” was given in Computer Engineering Department. In the course laboratories, Python[2] programming language was used, and the attending students have created various projects in Visual Python. The students projects were created in partial fulfilment of the requirements for receiving a credit for the laboratories. Based on the students projects, the present paper concerns modelling reality, visualizing real-world phenomena and writing simple educational games in Visual Python. Published in Proceedings of the INotice 2011 Conference, ISBN 978-83-7283-407-2 The Conference was held in June 2011 in Słok, Poland paper (PDF) in the conference proceedings presentation and movie from the conference

  11. Quantum-Inspired Evolutionary Algorithms in Search and Optimization
    R.Nowotniak
    Abstract: The presented research concerns a new class of artificial intelligence techniques, drawing inspiration from both the biological evolution and unitary evolution of quantum systems. Intensive studies in this new area (Quantum-Inspired Evolutionary Algorithms) have been conducted since the beginning of the last decade. Quantum computing provides a valuable source of inspiration to create new heuristic methods for searching and optimization. Additional random factors, inspired by the unique quantum phenomena (superposition of states, quantum parallelism, interference, probability amplitudes), introduce a “new dimension” to the evolutionary algorithms. […] Published in Proceedings of the Scientific Session of TUL PhD Students, ISBN 978-83-7283-411-9 The Session was held in April 2011 in Rogow, Poland abstract (PDF) from the Scientific Session booklet my presentation (PDF) from the Session

  12. Meta-optimization of Quantum-Inspired Evolutionary Algorithm
    R.Nowotniak, J. Kucharski
    Abstract: In this paper, a meta-optimization algorithm, based on Local Unimodal Sampling (LUS), has been applied to tune selected parameters of Quantum-Inspired Evolutionary Algorithm for numerical optimization problems coded in real numbers. Tuning of the following two parameters has been considered: crossover rate and contraction factor. Performance landscapes of the algorithm meta-fitness have been approximated and numerical experiments have been conducted on four high-dimensional optimization problems. The tuned algorithm outperformed the algorithm with initially proposed parameters in the conducted experiments. Published in Proceedings of the XVII International Conference on Information Technology Systems, ISBN 978-83-7283-378-5 paper (PDF) in the conference proceedings presentation (and two animations) and screencast from the conference

  13. Building Blocks Propagation in Quantum-Inspired Genetic Algorithm
    R.Nowotniak, J. Kucharski
    Abstract: This paper presents an analysis of building blocks propagation in Quantum-Inspired Genetic Algorithm, which belongs to a new class of metaheuristics drawing their inspiration from both the biological evolution and unitary evolution of quantum systems. The expected number of quantum chromosomes matching a schema has been analysed and a random variable corresponding to this issue has been introduced. The results have been compared with Simple Genetic Algorithm. Also, it has been presented how selected binary quantum chromosomes cover a domain of one-dimensional fitness function. preprint (PDF) from Scientific Bulletin of Academy of Science and Technology, Automatics, 2010 presentation and poster on SŁOK 2010 conference

  14. Survey of Quantum-Inspired Evolutionary Algorithms
    R.Nowotniak
    Abstract: This paper presents a concise survey of a new class of metaheuristics, drawing their inspiration from both: biological evolution and unitary evolution of quantum systems. In the first part of the paper, general concepts behind quantum-inspired evolutionary algorithms have been presented. In the second part, a state of the art of this field has been presented and a literature review has been conducted. Published in Proceedings of the FIMB PhD students conference ISSN 2082-4831 paper (PDF ) in the conference proceedings presentation from the conference

  15. Comparison of Algorithms for Simultaneous Localization and Mapping Problem for Mobile Robot
    S.Jeżewski, M. Łaski, R. Nowotniak
    Abstract: This paper presents a comparison of selected algorithms for simultaneous localization and mapping (SLAM) problem in mobile robotics. Results of four general metaheuristics, Simple Genetic Algorithm, Particle Swarm Optimization, Quantum-Inspired Genetic Algorithms and Genetic Algorithm with Quantum Probability Representation, have been compared to results of classical, analytic method in this field, Iterative Closes Points algorithm. In the experiments the same objective function, drawn from Iterative Closest Points algorithm, has been used. Two situations have been considered: local and global localization problems of mobile robot. Both problems are import and often critical for successful navigation of robot in environment. preprint (PDF) from Scientific Bulletin of Academy of Science and Technology, Automatics, 2010 poster from SŁOK 2010 conference

  16. Application of Quantum Genetic Algorithms in Feature Selection Problem (in Polish)
    Ł. Jopek, R. Nowotniak, M. Postolski, L. Babout, M. Janaszewski
    Abstract: In the article, a feature selection problem for k-NN classifier in image segmentation has been analyzed. Feature selection has been considered as a two criteria combinatorial optimization problem. An objective of optimization process was to find an image points’ features subset, allowing good quality of segmentation in satisfactory time. A fitness function for features subsets has been proposed, taking into account time of features calculation and quality of segmentation. Three population-based heuristic methods of optimization have been compared: simple genetic algorithm and its two modifications, inspired by principles of quantum computing: QiGA (Quantum-Inspired Genetic Algorithm) and GAQPR (Genetic Algorithm with Quantum Probability Representation). Results of experiments with artificial and tomography textures have been presented. Published in Scientific Bulletin of Academy of Science and Technology, Automatics, 2009 ISSN 1429-3447 paper (PDF, in Polish) presentation and poster on SŁOK 2009 conference June 24, 2009

  17. On The Evolutionary Design of Quantum Algorithms (in Polish)
    R. Nowotniak
    presentation on Computer Engineering Department seminar text of my speech (in Polish ) poster (in Polish ) on XVI International Conference on Information Technology Systems October 1, 2008

  18. Quantum Teleportation
    R. Nowotniak
    presentation (in Polish ) Students Scientific Group seminar, Institute of Computer Science January 9, 2008

  19. Grover’s Quantum Search Algorithm
    R. Nowotniak
    presentation (in Polish ) my presentation on Institute of Computer Science seminar November 13, 2007

  20. Quantum Computing
    R. Nowotniak
    presentation (in Polish ), poster (in Polish ) and text of my speech (in Polish ) XV International Conference on Information Technology Systems October 26, 2007

  21. Quantum Computing in Numerical Python
    R. Nowotniak
    presentation (in Polish) Students Scientific Group seminar, Institute of Computer Science October 10, 2007

  22. Quantum Cooperation
    R. Nowotniak
    presentation (in Polish) Students Scientific Group seminar, Institute of Computer Science May 17, 2007

  23. Quantum Programming Languages
    R. Nowotniak
    presentation (in Polish) Students Scientific Group seminar, Institute of Computer Science January 3, 2007