Methods of Artificial Intelligence in Economical and Logistical Education
Methods of Artificial Intelligence in Economical and Logistical Education

Summary/Abstract: The artificial intelligence, also soft computing is more and more relevant in practice and their mystification causes plenty of misunderstandings. There's a need in secondary schools as well as in non-technical/scientific higher education to introduce them in an understandable way for later use. So in our lecture and article we show the applicability of soft computing in an easy to use simulation. In today's computer science education environment deterministic algorithms play a large role, the students learn, understand and maybe even know how to implement them. It would be important to make solutions, techniques, which don't rely on traditional deterministic observations known and understandable to not only students that are interested in computer science. The best solution is to reach the results of certain searching tasks. Since in our BigData based world these techniques are the core of procedures, there's a huge importance for the high-level understanding of these techniques in secondary school. There's no need to know the functioning of the core. In the first step importance of optimization tasks need to be introduced and made understood, as well as their practical problems and relevance in real life. In the next step it should be shown, that if we make concessions in the purpose of optimization (we show this through an example that this is achievable) with the help of other, less mathematically correct, approaches we get really good results. In the article we show with great detail through a case study an optimization task, show its relevance then we introduce a simulation tool which's AI based. With the use of this tool we go through all possible solution ways, and compare how two differing AI based systems behave. After the applied simulations, we rate the results for the students/listeners and examine their importance. We also draft in short how to interpret the simulation results and what their efficiency means. We show as well what role running time, (speed) step number, number of parameters as well as practicable parameters play. The article shows how we can use this in education through a case study.

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