Agent-based modeling and simulation have evolved as a powerful tool for modeling
complex systems, offering insights into emergent behaviors and interactions among diverse …

All basic processes of ecological populations involve decisions; when and where to move,
when and what to eat, and whether to fight or flee. Yet decisions and the underlying …

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

Urban environments, characterized by their complex, multi-layered networks encompassing
physical, social, economic, and environmental dimensions, face significant challenges in the …

Heightened concern regarding climate change and energy independence has increased
interest in plug-in electric vehicles as one means to address these challenges and …

Anthropogenic noise is now recognized as a major global pollutant. Rapidly burgeoning
research has identified impacts on individual behaviour and physiology through to …

Agent-based modeling is a simulation method in which autonomous agents interact with
their environment and one another, given a predefined set of rules. It is an integral method …

It is a main purpose of this book to demonstrate how a very considerable number of results
in probability theory can be derived from simple urn models. We have deliberately restricted …

Interest in L évy walks within the context of movement of organisms has recently soared, with
some now referring to this approach as the L évy walk/flight paradigm. The principal …

There is long-standing scientific interest in understanding purposeful movement by animals
and humans. Traditionally, collecting data on individual moving entities was difficult and time …