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EN
Modern computer simulation tools are based on different mathematical models. The simplest of these models are rank as rigid computational methods like statistics or probability mathematics. To flexible, more complex computational methods we can classify artificial neural systems, genetic algorithm or fuzzy sets. Without doubt usage of this second group of models are becoming more universal. They are classified as methods of artificial intelligence. With regard to their mechanisms of teaching, neural systems are used for the purpose of optimization. They allow to describe different non-linear structure of the data and to classify them in the appropriate way. Statistic methods do not show optimum results in the non-linear spaces and spaces that are dimensionally complex. Agent methods that are used in the intelligent systems make possible to precisely simulate reality. Reality with huge amount of objects that are on the different level of abstraction. They are used for example in rout planning by means of GPS system, in the planning different logistic processes, in the economics, in the forecasting of meteorological phenomenons etc. Common feature of all forecasting methods are mistakes connected with discrepancy of simulation results and real value. In the literature there is no researches in mentioned discipline. Results of optimization presented in the article are obtained using agent systems. These results refer to finding the shortest way to the defined extreme by studying level of route complexity (multiple, amount of extremes), time of studying, mistakes of defining appropriate extreme. To authenticate results in case of different tools to simulation, researches have been conducted with five different simulation computer programs.
EN
The evolution of consumer priorities focused on time-saving transactions, a personalized approach and the general move away from price as the sole and most important determinant of the quality of products and services have resulted in intensification of dynamic changes in e-commerce. This determined the need for technology which would effectively meet the requirements set by the market. Such a technology are intelligent program agents. The authors, through the award of selected applications of this class of systems in the analyzed market, indicate adaptability as a key for their efficient and effective functioning. This article presents different approaches to the issue of adaptability, which is a response to the need for agents to adapt to dynamic changes in the environment of e-commerce. Such a requirement is clear both from the need to modify their behavior in response to stimuli from the environment in which they operate and from the interaction with other agents in multi-agent systems.
PL
Ewolucja priorytetów konsumenckich, ukierunkowana na oszczędność czasu transakcji, spersonalizowane podejście i ogólne odejście od ceny jako jedynego i najważniejszego wyznacznika jakości produktów i usług spowodowały nasilenie dynamiki zmian zachodzących w handlu elektronicznym. Zdeterminowało to konieczność zastosowania technologii, która w sposób efektywny sprostałaby wymogom stawianym przez analizowany rynek. Technologią taką są inteligentni agenci programowi. Autorzy, poprzez wyróżnienie wybranych zastosowań systemów tej klasy w obszarze analizowanego rynku, wskazują na cechę adaptacyjności jako kluczową dla sprawnego i efektywnego funkcjonowania tych systemów. Niniejszy artykuł prezentuje różne podejścia do kwestii adaptacyjności, która jest odpowiedzią na konieczność dostosowania się agentów do dynamiki zmian zachodzących w środowisku e-commerce. Wymóg taki wynika zarówno z potrzeby modyfikowania swojego zachowania w reakcji na bodźce płynące z otoczenia, jak i z interakcji z innymi agentami w systemach wieloagentowych.
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