Although recent years bring massive astronomical surveys which have been extensivly searched, there are still
many mysteries burried in the data. We attempt to extract objects with untypical emission lines. Especialy those
with with weak and absent emission but without significant absorption. For that purpose we created database
which contains quasars spectra for a quick access and peaks detection code in R environment what we describe
in this article.
Finding interesting celestial objects among tens of thousands or even millions of recorded raw data is not an easy
task to implement. In this paper we speed up this process with high level nvidia cuda C++ template library
called Thrust, which makes our database with R interface much more evaluatedcient.
Standardization of the diagnostic process of insomnia is a highly important task in clinical practice, epidemiolog-
ical considerations and treatment outcomes assessment. In this paper we describe standard surveys relationships
within cluster groups with the same insomnia degrees.
Insomnia generally is defined as a subjective report of diagnoseculty falling sleep, diagnoseculty staying asleep, early
awakening, or nonrestorative sleep. It is one of the most common health complaints among the general population.
in this paper we try to find relationships between dirent insomnia cases and predisposing, precipitating, and
perpetuating factors following by pharmacological treatment.
In this paper data mining methods were applied to investigate features determining high quality pork meat. The aim of the study was analysis of conditionality of the pork meat quality defined in coherence with HDL and LDL cholesterol concentration, plasma leptin, triglycerides, plasma glucose and serum. The research was carried out on 54 pigs. originated from crossbreeding of Naima sows with P76-PenArLan boars hybrids line. Meat quality parameters were evaluated in samples derived from the Longissimus (LD) muscle taken behind the last rib on the basis: the pH value, meat colour, drip loss, the RTN, intramuscular fat and glycolytic potential. The results of this study were elaborated by using R environment and show that cluster and regression analysis can be a useful tool for in-depth analysis of the determinants of the quality of pig meat in homogeneous populations of pigs. However, the question of determinants of the level of glycogen and fat in meat requires further research.
Nowadays computers analyze medical data almost in every diagnose and treatment steps. We develop new technology which gives us better and more precise diagnose. We chose esophageal high resolution manometry with impedance (HRMI) which has been considered as a "gold standard" test for esophageal motility. HRMI is the next generation of manometry examination which is more sensitive and accurate to EFT. Examination allows physicians to get informations about esophageal peristalsis, amplitude and duration of the esophageal contraction and liquid/viscous bolus transit time from mouth through stomach. In 2008 we examined 80 patients using "old" EFT manometry and 80 patients in 2009 using high resolution manometry (HRMI). Everybody got manometry, endoscopy and X-ray examination. We asked about symptoms which we correlate and connect with data from EFT and HRMI. We tried to find a good algorithm for this purpose in order to do a simple and helpful tool for physician to make right diagnose and treatment decision. Connection between data and symptoms seems to be right and clear, but finding a good algorithm for given data is the main problem.
In this paper we explore the problem of communication and coordination in a team of intelligent game bots (aka embodied agents). It presents a tactical decision making system controlling the behavior of an autonomous bot followed by the concept of a team tactical decision making system controlling the team of intelligent bots. The algorithms to be introduced have been implemented in the Java language by means of Pogamut 2 framework, interfacing the bot logic with Unreal Tournament 2004 virtual environment.
Hormone parameters were determined in the serum of young addicted men in order to compare them with those obtained from the group of healthy subjects.
Three groups were investigated which were named opiates, mixed and control group.
Statistical and data mining methods were applied to obtain significant differences.
R package was used for all computation.
The determination of hormones parameters provide important information relative to impact of addiction.
Nowadays computers successfully analyze medical data giving results used for futher treatment. Every year we develop new technology which gives us better and more precise diagnose. We chose esophageal manometry (EFT) which has been considered as a "gold standard" test for the evaluation of esophageal motility. EFT allows physicians to get informations about esophageal peristalsis, amplitude and duration of the esophageal contraction and liquid/viscous bolus transit time from mouth through stomach. We examined 80 patients during 2008 year. Everybody got EFT, endoscopy and X-Ray examination. It was important to ask about symptoms which we correlate and connect with data from EFT. We tried to find a good algorithm for this job in order to do a simple and helpful tool for physician to make right diagnose. Connection between data and symptoms seems to be right and clear, but finding a good algorithm for given data is the main problem.
Blood pressure in childhood and adolescents is important indicator of good health and strong predictor of BP in adulthood. Genetic susceptibility, environmental and socioeconomic factors are related both with life style, obesity and cardiovascular risk including elevated BP. Increased body mass index is strictly correlated with BP, and obesity and overweight is main intermediate phenotype of childhood hypertension. However, despite current obesity epidemic available data do not fully support the hypothesis that it has resulted in increase of BP in children. We analysed data obtained from 7591 children participating in nation-wide health survey using data mining methodology. Results reveal relationships of obesity and high blood pressure with school environment characteristics.
Electric bioimpedance is one of methods to assess the hydrate status in hemodialyzed patients. It is also being used for assessing the hydration level among peritoneal dialysed patients, diagnosed with neoplastic diseases, patients after organ transplantations and the ones infected with HIV virus. During measurements sets were obtained from two groups, which were named a control (healthy volunteers) and test group (hemodialyzed patients). Its variables were the following: body mass index (BMI), intracellular water (ICW) - water volume inside you cells. (i.e., water in the "living" cells), extracellular water (ECW) - water volume outside the body cell mass (i.e., water in the "inactive" cells), total body water (TBW) - sum of ICW and ECW, ECW_TBW - ECW divided by TBW, ECW_mass - ECW divided by body mass, height, weight and age. Zscored, discretized data and data retrieval results were computed in R language environment in order to find a simple rule for recognizing health problems. The executed experiments affirm possibilities of creating good classifiers for detecting a proper patient with the help of medical data sets, but only with previous training.
Data obtained from modern movement analysis systems are challenging to analyse. There are several reasons for that:
large number of data obtained during the session, their multi-dimensionality, most of them are time-dependent, and often depend on each other.
During last years many different analytical techniques are used to deal with them in order to better understand the physiology and
pathophysiology of the human movement (especially gait). This paper presents most commonly used and promising techniques.
Universal Turing machine is a notional computing machine that stimulated work leading to the development of modern computers. The Turing machine operates on finite sequences of symbols by scanning a data type. The striking analogy to information-encoding biochemical reactions on information-carrying molecules was inspired to apply this methodology in neural networks. The essential feature of such approach is hybridization of pairs of complementary DNA strings and possibility to represent highly parallel selective operations, which can enable creating alternative, neural architectures. We describe our original model of molecular neuron based on DNA computing paradigm. During computation appropriate molecules are chosen, each specifying one of the finite number of initial states or processing elements.
The paper addresses a new implementation of genetic (or evolutionary) programming by using molecular approach. Our method is based on dataflow techniques in DNA computing. After description of fundamental operations on DNA molecules and construction of logical functions the genetic programming method is introduced. We propose a way to handle these graph encoding molecules and which can be considered a genetic programming algorithm; a short discussion about experiments in implementing parts of this procedure is added.
Self-assembly of DNA is considered a fundamental operation in realization of molecular logic circuits. We propose a new approach to implementation of data flow logical operations based on manipulating DNA strands. In our method the logic gates, input, and output signals are represented by DNA molecules. Each logical operation is carried out as soon as the operands are ready. This technique employs standard operations of genetic engineering including radioactive labelling as well as digestion by the second class restriction nuclease and Polymerase Chain Reaction~(PCR). To check practical utility of the method a series of genetic engineering experiments have been performed. The obtained information confirms interesting properties of the DNA-based molecular data flow logic gates. Some experimental results demonstrating implementation of a single logic NAND gate and only in one vessel calculation of a tree-like Boolean function with the help of the PCR are provided. These techniques may be utilized in massively parallel computers and on DNA chips.
Molecular computing is a new paradigm to perform calculations using nanotechnology. This paper presents the overall research direction from which molecular inference and expert systems are emerging. It introduces the subject matter and a general description of the problems involved. This includes selected methods of knowledge representation by DNA oligonucleotides, strategies of the inference mechanism, concept of the inference engine based on circular DNA molecules, particularly derived from plasmids, practical experience in DNA inference engine implementation, and discussion of the experimental results. The approach allows evaluating logical statements and drawing inferences for generating other statements via DNA computing. Series of experiments have been conducted to confirm practical utility of this approach. In these experiments, parameters of biochemical reactions were varied to determine truth/false recognition accuracy. In addition, we discuss the fundamental issues of inference engine and try to enhance physical insight into the dominating features of the approach proposed.
DNA computing is a new promising paradigm to develop an alternative generation of computers. Such approach is based on biochemical reactions using DNA strands which should be carefully designed. To this purpose a special DNA sequences design tool is required. The primary objective of this contribution is to present a virus-enhanced genetic algorithms for global optimization to create a set of DNA strands. The main feature of the algorithms are mechanisms included specially for searching solution space of problems with complex bounds. Formulae, describing bounds of power of sequences' sets, which satisfy criteria and estimation functions are expressed. A computer program, called Mismatch, was implemented in C++ and runs on Windows NT platform.
Self-assembly of DNA is considered a fundamental operation in realization of molecular logic circuits. We propose a new approach to implementation of data flow logical operations based on manipulating DNA strands. In our method the logic gates, input, and output signals are represented by DNA molecules. Each logical operation is carried out as soon as the operands are ready. This technique employs standard operations of genetic engineering including radioactive labeling. To check practical utility of the method a series of genetic engineering experiments have been performed. The obtained results confirm interesting properties of the DNA-based molecular data flow logic gates. This technique may be utilized in massively parallel computers.
The problem of improving the efficiency of Genetic Algorithms to search global optimum is considered. An approach based on applying Genetic Programming methodology to find the best structure of Genetic Algorithms for global optimization is described. It allows to obtain better results in comparison with standard Genetic Algorithms.
Molecular computation on DNA performs calculations using nanotechnology means during chemical reactions. With the help of silicon industry microfluidic processors were invented utilizing nano membrane valves, pumps and microreactors. These so called lab-on-a-chips combined together with molecular computing create molecular-systems-on-a-chips. This work presents an approach to implementation of logic systems on chips. It requires the unique representation of signals by DNA molecules. The main part of this work includes the concept of logic inference based on typical genetic engineering reactions. The presented method uses a lab-on-a-chip approach. Every microreactor of the lab-on-a-chip performs one unique operation on input molecules and can be connected by dataflow output-input connections to other ones.
Together with rapidly developing biotechnology, nanotechnology is a real opportunity to test new, maybe revolutionary ideas and algorithms of so called "soft hardware". Self-assembly feature of transforming nano-scale structures, such as DNA macromolecules but not only, from one state to another one in a very well defined way may offer the proper handle for nano-scale computations and play a central role in the development of nano-tech devices in the near future. The Turing machine analogy to information-encoding biochemical reactions on information-carrying molecules inspired our neural network experimental approximation. We describe our original model of molecular neuron network based on genetic laboratory operations.
DNA computing provides new molecular mechanism for storing and processing information. DNA macrostructures are bases of specially designed algorithms realized by so called soft hardware applications. To obtain these structures a special DNA sequences design tool is required. In this paper comparison of two such computer programs was provided. In our program a custom genetic algorithm with new hybrid operators was involved in creating a set of DNA chains. The second program written by Winfree makes random changes using a given set of short constant forbidden fragments.
Universal Turing machine is a notional computing machine that stimulated work leading to the development of modern computers. The Turing machine operates on finite sequences of symbols by scanning a data type. The striking analogy to information-encoding biochemical reactions on information-carrying molecules was inspired to apply this methodology in neural networks. The essential feature of such approach is hybridization of pairs of complementary DNA strings and possibility to represent highly parallel selective operations, which can enable creating alternative, neural architectures. We describe our original model of molecular neural network based on DNA computing paradigm. During computation appropriate molecules are chosen, each specifying one of the finite number of initial states or processing elements. The concept is illustrated by detecting the final state through one string solution. It is provided that presented neural networks may be connected to perform the molecular inference systems.
In this paper a new technique of sending data between molecular processors is presented. The molecular processor is a processing data unit. Its computation results have to be sent to other units in the form of addressed messages - tokens. Necessary experiments were performed. All operations were implemented in DNA. DNA processors and tokens were specially designed DNA strings. Results of experiments prove our assumptions.
The new algorithm of DNA computing for adding binary integer numbers is presented. It requires the unique representation of bits placed in test tubes treated as registers. Amplification step used for the carry operation allows in theory to add numbers at the same quantity of elementary operations, regardless of a number of bits used for representation. New notation proposed in this paper allows for efficient and abstract description of the technical operations on DNA.
DNA computing is a new paradigm to perform calculations using genetic engineering technology. This paper presents the overall research direction from which molecular inference and expert systems are emerging. It provides an introduction to the subject matter and a general description of the problems involved. This includes selected methods of knowledge representation by DNA strands, strategies of the inference mechanism, concept of the inference engine based on circular DNA molecules, particularly derived from plasmids, practical experience in DNA inference engine implementation, and discussion of the experimental results. The approach allows evaluating logical statements and drawing inferences for generating other statements via DNA computing.
In this paper we implement a new logic NAND gate using standard operations on DNA strands as well as digestion by the restriction nuclease class II. This concept despite some difficulties looks in general more elegant and can be utilized with fluorescent probes. Some experimental results demonstrating implementation of a single logic NAND gate are provided. The derived logic gates are proposed to be implemented on DNA chips.
In this paper we propose a new implementation of logic circuits based on molecular computing technique. Our method uses standard operations on DNA strands as well as digestion by the restriction nuclease S2. Some experimental results demonstrating implementation of a single logic NAND gate are provided. This concept despite some difficulties looks in general more elegant and can be utilized with fluorescent probes. The derived logic gates are proposed to implement combinational networks in test tubes.
In this paper the application of genetic programming to find the best set of parameters for the Cerebellar Model Articulation Controller (CMAC) is considered. CMAC is used in many fields (automatic control, image recognition, etc.) offering fast and robust learning along with local generalization capability. One of the main drawbacks of the model is that it has many adjustable parameters. This paper shows that genetic algorithm, tuned using the paradigm of genetic programming, is capable of finding the satisfactory parameters set for the CMAC model. Some preliminary experimental evaluations are presented. Conclusions and avenues for future work are finally discussed.
The problem of improving efficiency of Genetic Algorithms to search global optimum is considered. In this paper, we propose an approach which is based on Genetic Programming methodology to find the best structure of Genetic Algorithms for global optimization. The proposed approach has been implemented in C++ on a Pentium 90. We have conducted many experiments, some of them presented in this paper. The results show that the proposed approach is better than standard Genetic Algorithms or even Evolution Strategies and Controlled Random Search.
Przedstawiono przyszłe kierunki rozwoju nanoelektroniki i związane z tym technologie.
Opisano molekularne układy logiczne wywodzące się z DNA computingu oraz tradycyjnej elektroniki, a mogące stać się podstawą alternatywnych architektur komputerowych.
Obliczenia molekularne są nowym sposobem implementacji technik informacyjnych dokonywanych w probówkach w czasie reakcji chemicznych. Charakterystyczną cechą tego podejścia jest prowadzenie obliczeń na poziomie molekuł, które traktuje się jak procesory. W artykule przedstawiono podstawowe kierunki rozwoju i zastosowania obliczeń molekularnych, zwrócono uwagę na istotne z informatycznego punktu widzenia właściwości kwasu deoksyrybonukleinowego DNA, następnie scharakteryzowano operacje genetyczne wykorzystywane w implementacjach molekularnych, po czym wymienione zostały zalety i wady obliczeń molekularnych.
This Ph.D. thesis is one of the first works devoted to new DNA computing concepts. It describes unknown until now DNA hardware inventions for solving different logical problems. Information technology inspired by biology is a branch of so called computational intelligence, which contains such areas as artificial neural network, evolutionary computation, fuzzy logic systems. In the field of evolutionary computing new methodology of molecular computing has appeared lately. Molecules are utilized to represent and carry information. Biochemical reactions are just computational processes. In this approach DNA molecules carry information. Some author's algorithms solving logical problems were described using standard genetic engineering methods. Each algorithm is explained, implemented and experimentally verified. The new notation method of DNA computing and the new branch of computational processing on DNA called molecular genetic programming were introduced. There are also included new implementations of logical data flow systems and the new method of inference process based on circular DNA molecules. Introduced by author concepts are illustrated by many experimental results proving his assumptions.
Rozprawa jest jedną z pierwszych prac poświęconych nowym koncepcjom obliczeń molekularnych. Dotyczy ona nieznanych jeszcze rozwiązań sprzętowych na DNA czyli tzw. DNA computingu do rozwiązywania różnych problemów logiki. Techniki informacyjne inspirowane biologią stanowią ważny kierunek badawczy tzw. inteligencji obliczeniowej, która zawiera takie dziedziny jak sztuczne sieci neuronowe, obliczenia ewolucyjne, systemy rozmyte. W ramach obliczeń ewolucyjnych pojawiła się nowa metodologia prowadzenia obliczeń na poziomie molekularnym, gdzie cząsteczki wykorzystuje się do reprezentowania informacji, a reakcje biochemiczne odpowiadają procesom obliczeniowym.
W podejściu rozważonym w tej pracy jako nośnika informacji używa się cząsteczek kwasu DNA. Następnie korzystając ze standardowych metod inżynierii genetycznej opracowano różne algorytmy rozwiązujące problemy logiki. Szczególną uwagę zwrócono na własne koncepcje autora, które rozwinięto w postaci nieznanych dotąd algorytmów obliczeniowych na DNA. Algorytmy te są następnie wyjaśniane na podstawie przykładów implementacyjnych i weryfikowane eksperymentalnie. Wprowadzono nową metodę notacji zapisu informacji na DNA. Zarysowano również nowy kierunek badawczy związany z realizacją molekularnego programowania genetycznego. Zaprojektowano implementację programowania genetycznego na grafach przedstawiających funkcje logiczne z wykorzystaniem warsztatu inżynierii genetycznej. Przedstawiono nowe rozwiązania molekularnych bramek logicznych. Podano nieznaną dotąd metodę wnioskowania z wykorzystaniem kolistych cząsteczek DNA. Przedstawione przez autora koncepcje ilustrowane są licznymi wynikami doświadczalnymi, potwierdzającymi słuszność przyjętych założeń.
Bardzo często zadania inżyniera mogą zostać sformułowane jako problemy globalnej optymalizacji np.: takie, w których badana funkcja nie jest wypukła i posiada wiele lokalnych optimów w założonej przestrzeni parametrów. W mojej pracy dyplomowej rozwiązując problem globalnej optymalizacji zastosowałem algorytmy genetyczne. Poszukiwane jest globalne optimum np. minimum globalne funkcji wielu zmiennych z ograniczeniami kostkowymi (l - ograniczenie z lewej strony, r - ograniczenie z prawej strony danej zmiennej). W powstałym po zdefiniowaniu funkcji i ograniczeń obszarze parametrów (zmiennych) znajdują się dopuszczalne rozwiązania. Dana funkcja wielu zmiennych może mieć wiele optimów lokalnych i globalnych (jeśli tych drugich, to o takich samych wartościach funkcji). Cel zadania globalnej optymalizacji to znaleźć rozwiązanie, dla którego badana funkcja przyjmuje najmniejszą wartość - najmniejsze z minimów czyli optimum globalne. Nieliniowość funkcji objawia się zależnością nieliniową między wejściowymi parametrami np.: y = x*x + exp(x). Wyżej wspomniana metoda porównywana jest z innymi metodami stochastycznymi np.: strategiami ewolucyjnymi, metodą Price'a. Podjęta też została próba znalezienia najlepszego algorytmu genetycznego przy optymalizacji danej funkcji. W tym celu zastosowano metodę doboru najlepszej struktury algorytmu genetycznego za pomocą programowania genetycznego tzn.: programowanie genetyczne kreuje drzewa złożone z kolejnych operacji przeprowadzanych przez podrzędny algorytm genetyczny(drzewo opisuje ciąg operatorów genetycznych i ich parametrów dla pojedyńczej generacji) rozwiązujący problem globalnej optymalizacji.
The main concept of molecular computing dependeds on DNA self-assembly abilities and on modifying DNA with the help of enzymes during genetic operations. In the typical DNA computing a sequence of operations executed on DNA strings in parallel is called an algorithm, which is also determined by a model of DNA strings. This methodology is similar to the soft hardware specialized architecture driven here by heating, cooling and enzymes, especially polymerases used for copying strings. As it is described in this paper the polymerase Taq properties are changed by modifying its DNA sequence in such a way that polymerase side activities together with peptide chains, responsible for destroying amplified strings, are cut off. Thus, it introduces the next level of molecular computing. The genetic operation execution succession and the given molecule model with designed nucleotide sequences produce computation results and additionally they modify enzymes, which directly influence on the computation process. The information flow begins to circulate. Additionally, such modified enzymes are more suitable for nanoconstruction, because they have only desired characteristics. The experiment was conducted to confirm the possibilities of the suggested implementation. Laboratory results and perspectives of the proposed approach future use are discussed.
Implementation of the inference system based on DNA chains molecular computing is a new paradigm to perform calculations using nanotechnology means. This work presents new approach to implementation of inference engines based on DNA. It introduces the subject of inference methods designed to be used with molecular expert systems. The main part of this work includes the concept of the inference engine based on rule tree specially customized to allow implementation using deoxyribonucleic acid chains. The presented approach allows drawing inferences based on variable amount of predicates using most reliable techniques employed in standard operations of genetic engineering. In the presented approach cross cells are bases of multidimensional DNA structures. The experiment was conducted to confirm the capabilities of the suggested implementation. In addition, laboratory evaluation results and perspectives of further use of the proposed architectural approach are discussed.
It seems that when in near future the potentiality of traditional semiconductor technology will probably be depleted, the nanotechnology and self-assembling feature of molecules will become the research main trend. The first step in this direction is so called molecular computing as the result of interference between computer science and genetic engineering. In this paper we propose new concepts of molecular binary trees.
Adleman first pointed that computation using DNA is possible. Mills first reported approach to neural net representation by using DNA. In this paper we review our original model of molecular neural network based on DNA computing paradigm. During computation appropriate molecules are chosen, each specifying one of the finite number of initial states or processing elements. We present our model of DNA lattices. The concept is illustrated by detecting the final state through one string solution. It is provided that presented neural networks may be connected to perform the molecular inference systems.
DNA computing is a striking new information technology based on chemical reactions in tubes utilizing specially designed with a help of computer programs DNA polymers. This methodology provides new molecular mechanism for storing and processing information. DNA macrostructures are bases of specially designed algorithms realized by so called soft hardware applications. To obtain these structures a special DNA sequences design tool is required. A custom genetic algorithm with new hybrid operators was involved in creating a set of DNA strings. Changes in the input files and examples of string generation were introduced.
In this paper the method of automatic string sets generation for DNA computing was described. A computer program written in C++ called Mismatch with our new improvements was used. We described changes in the input files and examples of string generation. These new optimized DNA structures are useful in the implementation of molecular inference systems. The models of DNA computing are helpful in developing alternative generation of extremely miniaturized computers.
W artykule przedstawiono nową metodologię przetwarzania informacji za pomocą reagujących ze sobą cząsteczek biochemicznych. Podejście takie nazywane jest obliczeniami molekularnymi, a reagujące cząsteczki pełnią rolę procesorów. Obliczenia molekularne wykorzystują techniki inżynierii genetycznej, a jako materiał do zapisu i przetwarzania informacji używa się przeważnie cząsteczek kwasu deoksyrybonukleinowego. W pracy opisano właściwości obliczeń molekularnych oraz możliwości wykorzystania tej metody w technice komputerowej i programowaniu. Szczególną uwagę zwrócono na koncepcje obliczeń molekularnych opracowane przez autorów.
Techniki informacyjne inspirowane biologicznie stanowią główny kierunek badawczy tzw. inteligencji obliczeniowej, która zawiera takie dziedziny jak sztuczne sieci neuronowe, obliczenia ewolucyjne, systemy rozmyte. W ramach obliczeń ewolucyjnych pojawiła się niedawno nowa metodologia prowadzenia obliczeń na poziomie molekularnym z wykorzystaniem reakcji chemicznych. W niniejszej pracy przedstawiono podstawowe koncepcje oraz modele obliczeń molekularnych z wykorzystaniem standardowych metod inżynierii genetycznej na bazie kwasu deoksyrybonukleinowego.
In this paper self-programming of algorithms is considered. Genetic Algorithms are developed under control of Genetic Programming. It is approved that this methodology leads to finding the best structure of optimization algorithm, which searches the global optimum in multidimensional functions. The proposed approach has been implemented in C++ on a Pentium 90. Many experiments have been conducted. Some of them are presented in this paper. The results show that this new method allows to find better structures of Genetic Algorithms than standard ones or even those of Evolution Strategies.
Temat artykułu związany jest z tematem "Zautomatyzowane systemy dowodzenia i kierowania". Opisuje wykorzystanie programowania genetycznego w optymalizowaniu algorytmów działania samodzielnych programów pobierających informacje z komputerów w sieci telekomunikacyjnej łączącej stanowiska dowodzenia z systemami baz danych zapisujących uzyskane z systemów rozpoznania położenie i rodzaje wojsk nieprzyjaciela.
W ostatnich latach wśród badaczy zajmujących się rozwojem technik komputerowych obserwuje się zainteresowanie rozwiązaniami inspirowanymi biologicznie. Wynika to z faktu, że człowiek - najwyższa forma życia w świecie przyrody - wykazuje zdolności przetwarzania informacji przewyższające możliwości najszybszych komputerów. Dotyczy to w szczególności takich zagadnień jak rozpoznawanie obrazów i mowy, rozwiązywanie problemów, uczenie się, itp. Inspiracją dla badaczy jest przede wszystkim ludzki mózg, w którym poszczególne neurony połączone w sieci stanowią podstawę dla modelowania sztucznych sieci neuronowych i rozproszonych systemów o przetwarzaniu równoległym. Innego rodzaju inspiracją jest dostosowywanie się gatunków do zmieniającego się środowiska, co dało podstawy algorytmów ewolucyjnych. Z kolei potraktowanie przyrody w szerszym kontekście prowadzi do powstania nowej dziedziny, zwanej sztucznym życiem. Wymienione koncepcje z punktu widzenia przetwarzania informacji i techniki komputerowej tworzą informatyczne narzędzia inspirowane biologicznie.
W dotychczasowym rozwoju informatyki najwięcej uwagi zyskały sztuczne sieci neuronowe, które dały początek tzw. neurokomputerom. Interesujące jest potraktowanie wymienionych narzędzi inspirowanych biologicznie w sposów całościowy w kontekście systemów hybrydowych, które mogą okazać się ciekawą alternatywa dla istniejących systemów informatycznych. Technika komputerowa wchodzi szerokim frontem niemal w każdą dziedzinę działalności człowieka. Ponieważ narzędzia inspirowane biologicznie wnoszą nową jakość do obliczeń komputerowych, dlatego oczekuje się, że mogą one przyczynić się do zwiększenia efektywności działania komputerów w takich dziedzinach, w których dotychczasowa ich skuteczność nie jest zadowalająca. Z tego względu interesujące jest rozważenie możliwości zastosowania narzędzi inspirowanych biologicznie w zarządzaniu, czemu poświęcony jest niniejszy artykuł.
The problem of scheduling tasks of a parallel program on multiprocessor system is considered. An approach to the problem based on applying Genetic Programming methodology to find the best structure of Genetic Algorithms for the scheduling problem is described. It allows to obtain better results in comparison with standard Genetic Algorithms.