Spatial Validation of Agent-Based Models

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 ...

Path dependence and the validation of agent-based spatial models of land use

In this paper, we identify two distinct notions of accuracy of land-use models and highlight a tension between them. A model can have predictive accuracy: its predicted land-use pattern can be highly correlated with the actual land-use pattern. A model can also have process accuracy: the process by which locations or land-use patterns are determined can be consistent with real world processes. ...

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

A Bayesian Approach to the Validation of Agent-Based Models

The rapid expansion of agent-based simulation modeling has left the theory of model validation behind its practice. Much of the literature emphasizes the use of empirical data for both calibrating and validating agent-based models. But a great deal of the practical effort in developing models goes into making sense of expert opinions about a modeling domain. Here we present a unifying view whic...