Multi-agent systems (MASs) are defined as a group of interacting entities or agents sharing a common environment that changes over time, with capabilities of perception and action, and the mechanisms for their coordination provide a modern perspective on systems that traditionally were regarded as centralized. The main characteristics of agents are learning and adaptation. In the last few years, MASs have received tremendous attention from scholars in different fields. However, there are still challenges faced by MASs and their integration with machine learning (ML) methods. The primary goal of the study is to provide a broad review of the current developments in the field of MASs combined with ML methods. First, we present features of MASs considering the ML perspective. Second, we provide a classification of applications of MASs combined with ML methods. Third, we present a density map of applications in E-learning, manufacturing, and commerce. We expect this study to serve as a comprehensive resource for researchers and practitioners in the area.

E-commerce emerged as consequence of electronic transactions developed on 60's, but real boom was observed during 90's along with Internet common use. Complexity sciences approach has several advantages for e-Commerce study. This study addresses the need for modelling and simulation (M&S) of e-commerce supply chain as complex adaptive system (CAS) but with a novel application in the field of hybrid M&S, integrating top-down and bottom-up approaches using synthetic microanalysis, to perform simulation experiments to find natural emergent properties at certain levels as result of the interactions between the constituent parts, so far lacking in the scientific literature. Although previous researchers conducted simulation studies into the e-commerce supply chain as CAS, they all focused on applying agent-based simulation approach only. First, we conduct the literature review on main features of CAS, M&S of CAS as well as the e-commerce supply chain conceptualized as CAS and their modelling and simulation evolution. Second, we present a novel hybrid M&S methodology for integrating top-down and bottom-up approaches using synthetic microanalysis. Then, we applied the methodology to an omnichannel retail business case study. Finally, our concluding remark and future work are drawn. The novel methodology proved to be useful for anticipate business decisions on e-commerce supply chain.Povzetek: Ta študija s pomočjo hibridne metodologije obravnava potrebo po modeliranju in simulaciji eposlovne dobavne verige kot kompleksnega prilagodljivega sistema.