Mar 09, 2018 | 15:00—15:30
Multi-agents systems (MAS) have been introduced in the field of artificial intelligence (AI) to denote a set of entities which act and interact in intelligent (i.e., often: rational) ways. Beyond AI, the application of results concerning MAS involves various other scientific disciplines, such as: biology; sociology; finance; and economics.
In the literature, a large number of models have been proposed to describe the dynamics of MAS. Most of these are based on simulations, limiting their validity to the particular scenarios considered and to the specific choice of simulation parameters: In order to derive more robust results, it is of interest to identify viable analytic approaches.
Our framework is inspired by mathematical kinetic theories, with the aim to obtain analytic results on the dynamics of MAS from the description of the effects of single interactions among agents. KTMAS can incorporate different types of interactions, and it can be used to describe the dynamics of different features of MAS.
We present our research in the scope of the new disciplines of econophysics, which can be used to model wealth evolution, and sociophysics, which can be adopted to characterise opinion evolution.