Behavior-driven agent-based models of spatial systems

Predicting Behavior in Agent-Based Models for Complex Systems

Many important real-world systems feature a population of interacting objects (e.g., financial markets, traffic). These systems often exhibit unexpected macroscopic behavior whose existence would have been hard to predict based solely on a knowledge of the microscopic properties of an individual (e.g., market crashes, traffic jams). Despite the lack of a universally accepted definition of compl...

The complexity of agent-based spatial models

models aim to demonstrate some basic social process that may lie behind many areas of social life. A good example is Epstein and Axtell’s pioneering book on Growing Artificial Societies (Epstein et al., 1996), which presents a series of successively more complex models of the economics of an artificial society. ... With these models, there is no intention to model any particular empirical case ...

Agent-Based Modeling of Complex Spatial Systems

We are interested in the physics of cyberspatial objects (events, agents, processes) whose behaviors unfold in cyberspace, a manifold where geospatial, infospatial and temporal indices are required to distinguish one object from another and, for a given object, one state from another. Consequently, we propose a cyberspace-time (CST) reference framework for describing the dynamics of cyberphysic...

Agent-based Models and the Spatial Sciences

Agent-based models (ABMs) are used in the spatial sciences as building-blocks for computer simulation. ABMs have a range of advantageous attributes, not least of which is their flexibility in representing dynamic and highly adaptive physical or human phenomena. ABMs facilitate the exploration of ideas about the myriad of ways that geographical systems develop, behave, interact and evolve, often...

Computational Laboratories for Spatial Agent - Based Models