A probe mechanism to couple spatially explicit agents and landscape models in an integrated modelling framework

Many environmental, ecological, and social problems require investigation using a mixture of landscape models, individual‐based models, and some level of interaction between them. Few simulation‐modelling frameworks are structured to handle both styles of model in an integrated fashion. ECO‐COSM is a framework that is capable of handling complex models with both landscape and agent components. Its Probe‐based architecture allows model components to have controlled access to the state of other components. The ProbeWrapper is a modification of this common design approach which allows alterations to the state retrieved from the model and is a critical component of ECO‐COSM's broad modelling capability. It allows agents to apply perceptual filters or measurement errors to their observations of the landscape, or apply decision‐making strategies in the face of incomplete or uncertain observations. ECO‐COSM is demonstrated with a landscape model of metapopulation dynamics, an agent model of squirrel dispersal, and a coupled landscape‐agent model to evaluate field‐data‐acquisition strategies for identifying nutrient or contaminant hotspots.

[1]  Cyril S. Ku,et al.  Design Patterns , 2008, Wiley Encyclopedia of Computer Science and Engineering.

[2]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[3]  H. Randy Gimblett,et al.  Integrating geographic information systems and agent-based modeling techniques for simulating social and ecological processes , 2001 .

[4]  James D. Westervelt,et al.  Modeling mobile individuals in dynamic landscapes , 1999, Int. J. Geogr. Inf. Sci..

[5]  Shivanand Balram,et al.  Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes , 2003, The Professional Geographer.

[6]  Ginger Booth,et al.  Gecko: A Continuous 2D World for Ecological Modeling , 1997, Artificial Life.

[7]  Martin,et al.  UML for Java¿ Programmers , 2003 .

[8]  George J. Klir,et al.  Fuzzy sets and fuzzy logic - theory and applications , 1995 .

[9]  Mario E Inchiosa,et al.  Overcoming design and development challenges in agent-based modeling using ascape , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[10]  Jianguo Liu,et al.  Individual-Based Modeling , 2002 .

[11]  P. Hraber,et al.  Community assembly in a model ecosystem , 1997 .

[12]  J. Banks,et al.  Discrete-Event System Simulation , 1995 .

[13]  Grady Booch,et al.  Object-oriented analysis and design with applications (2nd ed.) , 1993 .

[14]  Donald L. DeAngelis,et al.  Multimodeling: new approaches for linking ecological models , 2006 .

[15]  Richard Stillman,et al.  Individual‐based Modeling and Ecology.Princeton Series in Theoretical and ComputationalBiology.ByVolker Grimmand, Steven F Railsback.Princeton (New Jersey): Princeton University Press.$99.50 (hardcover); $49.50 (paper). xvi + 428 p; ill.; index. ISBN: 0–691–09665–1 (hc); 0–691–09666–X (pb). 2005. , 2006 .

[16]  Patrick A. Zollner,et al.  Using body size to predict perceptual range , 2002 .

[17]  G. Booth,et al.  Modelling food web complexity: The consequences of individual-based, spatially explicit behavioural ecology on trophic interactions , 1997, Evolutionary Ecology.

[18]  G. Huse Individual‐based Modeling and Ecology , 2008 .

[19]  Nils B. Weidmann,et al.  Technical Note: Evaluating Java Development Kits for Agent-Based Modeling , 2005, J. Artif. Soc. Soc. Simul..

[20]  J. Holland Echoing emergence: objectives, rough definitions, and speculations for ECHO-class models , 1999 .

[21]  Vincent B. Robinson,et al.  Spatially Explicit Individual-Based Ecological Modeling with Mobile Fuzzy Agents , 2005 .

[22]  Gerald W. Both,et al.  Object-oriented analysis and design with applications , 1994 .

[23]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[24]  Jon M. Kerridge,et al.  PEDFLOW: Development of an Autonomous Agent Model of Pedestrian Flow , 2001 .

[25]  Andy South,et al.  Extrapolating from individual movement behaviour to population spacing patterns in a ranging mammal , 1999 .

[26]  Robert D. Holt,et al.  Linking Contemporary Vegetation Models with Spatially Explicit Animal Population Models , 1995 .

[27]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[28]  Ling Bian,et al.  The representation of the environment in the context of individual-based modeling , 2003 .

[29]  Brian Foote,et al.  Designing Reusable Classes , 2001 .

[30]  Dimitar P. Filev,et al.  Fuzzy SETS AND FUZZY LOGIC , 1996 .

[31]  Sean Luke,et al.  MASON: A Multiagent Simulation Environment , 2005, Simul..

[32]  William Rand,et al.  Spatial process and data models: Toward integration of agent-based models and GIS , 2005, J. Geogr. Syst..

[33]  Miles T. Parker,et al.  What is Ascape and Why Should You Care? , 2001, J. Artif. Soc. Soc. Simul..

[34]  H. Caswell,et al.  Disturbance, interspecific interaction and diversity in metapopulations , 1991 .

[35]  William H. McDowell,et al.  Biogeochemical Hot Spots and Hot Moments at the Interface of Terrestrial and Aquatic Ecosystems , 2003, Ecosystems.

[36]  Phillip Andrew Graniero,et al.  The effect of spatiotemporal sampling strategies and data acquisition accuracy on the characterization of dynamic ecological systems and their behaviours , 2001 .

[37]  Vincent B. Robinson Using fuzzy spatial relations to control movement behavior of mobile objects in spatially explicit ecological models , 2002 .

[38]  Vincent B. Robinson,et al.  An Object-Oriented Approach to Managing Fuzziness in Spatially Explicit Models Coupled to a Geographic Database , 2005 .

[39]  S. Forrest,et al.  Modeling Complex Adaptive Systems with Echo , 1994 .

[40]  M. Batty,et al.  Local movement: agent-based models of pedestrian flows , 1998 .

[41]  E. J. Comiskey,et al.  Individual-Based Models on the Landscape: Applications to the Everglades , 1999 .

[42]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[43]  Robert Tobias,et al.  Evaluation of free Java-libraries for social-scientific agent based simulation , 2004, J. Artif. Soc. Soc. Simul..

[44]  G. Booth Gecko: A continuous 2d world for ecological modeling , 1997 .

[45]  Jo Wood Java Programming for Spatial Sciences , 2002 .

[46]  Nelson Minar,et al.  The Swarm Simulation System: A Toolkit for Building Multi-Agent Simulations , 1996 .

[47]  Stephen Travis Pope,et al.  A cookbook for using the model-view controller user interface paradigm in Smalltalk-80 , 1988 .