The advent of artificial intelligence has led to a growing emphasis on data-driven modeling
in macroeconomics, with agent-based modeling (ABM) emerging as a prominent bottom-up …

The advent of the Web has brought about a paradigm shift in traditional economics,
particularly in the digital economy era, enabling the precise recording and analysis of …

Scientists and engineers seek to understand how real-world systems work and could work
better. Any modeling method devised for such purposes must simplify reality. Ideally …

We present a machine learning framework bridging manifold learning, neural networks,
Gaussian processes, and Equation-Free multiscale approach, for the construction of …

Large language models (LLMs) are becoming a significant source of content generation in
social networks, which is a typical complex adaptive system (CAS). However, due to their …

The current macroeconomic models of the circular economy rely on the unrealistic
assumption that materials can be recycled infinitely, often ignoring price and demand …

The dynamics of pedestrian behavior within the built environment represent a multifaceted
and evolving field of study, profoundly influenced by shifts in industrial and commercial …

During the past decade, world economic development was coupled with disruptive
challenges. Among them, digitalisation and new forms of globalisation represent a potential …

From a pioneer in the field of complexity science and chaos theory, a plan for solving the
world's most pressing problems" Farmer convincingly argues that by using big data and …

Human capital theory is the dominant theory of education in economics. Earlier writers such
as Adam Smith, John Stuart Mill and Alfred Marshall highlighted a variety of roles for …