Paul M. Torrens

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Urban simulation has undergone somewhat of a transformation in recent years. The field has emerged from an ‘‘evolutionary’’ phase, which has spanned the last two decades. A ‘‘new wave’’ of urban models have begun to take center stage, influenced by technologies such as cellular automata (CA) and multi-agent systems (MAS) (Batty, Couclelis, & Eichen, 1997;(More)
A novel approach to automata-based modeling for spatial systems is described: geographic automata and Geographic Automata Systems. We detail a framework that takes advantage of the formalism of automata theory and GI Science to unite cellular automata and multi-agent systems techniques, and provides a spatial approach to bottom-up modeling of complex(More)
Suburban sprawl, a relatively recent phenomenon, is among the most important urban policy issues facing contemporary cities. To date, a well-accepted rationale has not been settled on for explaining and managing the causes of sprawl. Our contention is that consideration of geography is essential—that geographical explanations offer much potential in(More)
Debate regarding suburban sprawl in urban studies is contentious. It is fair to say that the phenomenon is not fully understood to satisfaction in the academic, policy, or planning communities and there are a host of reasons why this may be the case. Characterization of sprawl in the literature is often narrative and subjective. Measurement is piecemeal and(More)
(Originally and inspirationally entitled, 'A hybrid geocomputation model for operational land-use and transport simulation.) ABSTRACT There are indications that the current generation of simulation models in practical, operational uses has reached the limits of its usefulness under existing specifications. The relative stasis in operational urban modeling(More)
The emergence of computational social science has had a transformative influence on the geographical sciences, integrating diverse themes of scholarship and allying it with the pursuit of grand challenges in the physical, natural, and life sciences. Geography has benefitted from many of these developments and has, in turn, catalyzed significant advances and(More)
We introduce a novel scheme for automatically deriving synthetic walking (locomotion) and movement (steering and avoidance) behavior in simulation from simple trajectory samples. We use a combination of observed and recorded real-world movement trajectory samples in conjunction with synthetic, agent-generated, movement as inputs to a machine-learning(More)
The goal of an autonomic system is to self-manage itself and adjust its actions in the face of environmental changes. In this paper, we adopt a multiagent approach to developing an Autonomic Information System. The aim of this Autonomic Information System (AIS) is to provide an information system that can adjust its processing algorithms and/or information(More)