In contemporary global knowledge based society there are scorching needs for new knowledge and unprecedented vision of future development. Author is focuses attention to new possibilities of fostering creative abilities and gaining new socio-economic knowledge by the assistance of ICT, Internet and mainly by using products and services of computational intelligence. His method used is prevailingly new knowledge creation by experimentation in virtual laboratories. In using conventional methods, he combines inductive and deductive methods as set up for developing mental models (...) from up to down and bottom to up. Because in socio-economic branches it is very difficult and even almost wholly impossible to do experiments in objective reality the experimentation by the assistance of computational intelligence is promising advance in gaining new socioeconomic knowledge in contemporary complex world. Using such new approaches, methods and tools is the main scientific aim of the author. He uses convictive demonstration of successful using these unprecedented possibilities in gaining deeper knowledge about complex evolutionary phenomena. The distinction of such knowledge is against conventional one is consisting in very deep understanding of complex socio-economic dynamics. Using meant knowledge acquisition approaches is promising in quality and in abiding knowledge and skill of single individuals but the extraordinary progress of creative knowledge based society fostered by using them in advanced webs is useful for whole society. (shrink)

In economics there are several complex learning themes and tasks connected with them difficult for deeper understanding of the learning subject. These are the reasons originating serious learning problems for students in the form of Virtual Environment because deeper understanding requires high level mathematical skills. Actually the most important feature for discerning this part of economics is the set of qualitative shapes emerging in discrete dynamic systems when they are undergoing iterations and/or experimentation with parameters and initial coordinates of variables. (...) Among such shapes there are: - trajectories in evolving time; - trajectories in R2 of two variables; - cobweb portraits; - one control parameter bifurcation with first and/or with second variables; - two control parameters bifurcation in R2 ; - cycles; - basin of attraction of two variables; - one Lyapunov’s exponent against some of control parameters; - Lyapunov’s exponents with two control parameters in R2; - absorbing area with possibility to create critical curves and/or attractors. The hope is that products of computational intelligence may help them solve such problems. Naturally, the meant complex economic problems and tasks have discrete, qualitative and nonlinear nature resulting in increased level of difficulties. So with the term used in the head of this paper one has to understand narrowly: “qualitative nonlinear computational economics”. For better understanding the very nature of the problem we are using as appropriate example actual simulation of the model of new ICT products monopolies in virtual laboratory built in the routines setting dominantly in the software iDMC. (shrink)

There are several ontological and consequently also methodological mistakes in contemporary mainstream economics. Among them, the so-called ergodic axiom is play significant role. It is understandable that the real economy elaborated as formalized mental model looks like dynamic system on first sight. However, that is right only of dynamical systems in mathematical formalism. Economy that is in our understanding societal and/or collective economy is complex evolving organism. If we imagine such organism in the form of dynamical system that is as (...) clear mathematical formalism, we are losing their crucial authentic character. The significant irredeemable attribute of societal economy is lying in his complex evolving network process character created by large population of people with different decision-making and complex realizing among them. Going from these imaginations the two entities in a question that is dynamical system with their ergodicity and societal economic organism as complex evolving network are qualitative very different ones. That is the reason why we cannot accede with endeavours to draw on living economy straitjacket of ergodic axiom. To articulate that cause by other words ergodic dynamical systems are applicable for physical and partly for chemical entities and only scarcely are fit for living organisms. On the other hand however, as clear method the ergodic dynamical system have good applying for didactical approaches in economics where helping in better understanding some types of complexities in dynamics. The purpose of that essay is to discuss problems around usability of ergodic dynamical system theory and methods in economics in the age of advanced ICT knowledge based society. (shrink)