Coverart for item
The Resource Empirical Agent-Based Modelling - Challenges and Solutions : Volume 1, The Characterisation and Parameterisation of Empirical Agent-Based Models, edited by Alexander Smajgl, Olivier Barreteau, (electronic resource)

Empirical Agent-Based Modelling - Challenges and Solutions : Volume 1, The Characterisation and Parameterisation of Empirical Agent-Based Models, edited by Alexander Smajgl, Olivier Barreteau, (electronic resource)

Label
Empirical Agent-Based Modelling - Challenges and Solutions : Volume 1, The Characterisation and Parameterisation of Empirical Agent-Based Models
Title
Empirical Agent-Based Modelling - Challenges and Solutions
Title remainder
Volume 1, The Characterisation and Parameterisation of Empirical Agent-Based Models
Statement of responsibility
edited by Alexander Smajgl, Olivier Barreteau
Creator
Contributor
Editor
Subject
Language
eng
Summary
This instructional bookshowcases techniques to parameterise human agents in empirical agent-based models(ABM). In doing so, it provides a timely overview of key ABM methodologies and the most innovative approaches through a variety of empirical applications. It features cutting-edge research from leading academics and practitioners, and will provide a guide for characterising and parameterising human agents in empirical ABM.In order to facilitate learning, this text shares the valuable experiences of other modellers in particular modelling situations. Very little has been published in the area of empirical ABM, and this contributed volume will appeal to graduate-level students and researchers studying simulation modeling in economics, sociology, ecology, and trans-disciplinary studies, such as topics related to sustainability. In a similar vein to the instruction found in a cookbook, this text provides the empirical modeller with a set of 'recipes' ready to be implemented. Agent-based modeling (ABM) is a powerful, simulation-modeling technique that has seen a dramatic increase in real-world applications in recent years. In ABM, a system is modeled as a collection of autonomous decision-making entities called agents. Each agent individually assesses its situation and makes decisions on the basis of a set of rules. Agents may execute various behaviors appropriate for the system they represent--for example, producing, consuming, or selling. ABM is increasingly used for simulating real-world systems, such as natural resource use, transportation, public health, and conflict.Decision makers increasingly demand support that covers a multitude of indicators that can be effectively addressed using ABM. This is especially the case in situations where human behavior is identified as a critical element. As a result, ABM will only continue its rapid growth. This is the first volume in a series of books that aims to contribute to a cultural change in the community of empirical agent-based modelling. This series will bring together representational experiences and solutions in empirical agent-based modelling. Creating a platform to exchange such experiences allows comparison of solutions and facilitates learning in the empirical agent-based modelling community. Ultimately, the community requires such exchange and learning to test approaches and, thereby, to develop a robust set of techniques within the domain of empirical agent-based modelling. Based on robust and defendable methods, agent-based modelling will become a critical tool for research agencies, decision making and decision supporting agencies, and funding agencies. This series will contribute to more robust and defendable empirical agent-based modelling
Member of
Cataloging source
IT-FiEUI
http://library.link/vocab/creatorName
Smajgl, Alexander
Image bit depth
0
Literary form
non fiction
http://library.link/vocab/relatedWorkOrContributorName
  • Barreteau, Olivier.
  • SpringerLink (Online service)
Series statement
Springer eBooks
http://library.link/vocab/subjectName
  • Statistics
  • Computer simulation
  • Mathematical statistics
Label
Empirical Agent-Based Modelling - Challenges and Solutions : Volume 1, The Characterisation and Parameterisation of Empirical Agent-Based Models, edited by Alexander Smajgl, Olivier Barreteau, (electronic resource)
Link
https://eui.idm.oclc.org/login?url=http://dx.doi.org/10.1007/978-1-4614-6134-0
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier.
Color
not applicable
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent.
Contents
Empiricism and agent-based modelling -- A case study on characterising and parameterising an agent-based integrated model of recreational fishing and coral reef ecosystem dynamics -- An Agent-Based Model of Tourist Movements in New Zealand -- Human--ecosystem interaction in large ensemble model systems -- Using Spatially Explicit Marketing Data to Build Social Simulations
Control code
978-1-4614-6134-0
Dimensions
unknown
Extent
XIII, 249 pages 30 illustrations, 20 illustrations in color.
File format
multiple file formats
Form of item
electronic
Governing access note
Use of this electronic resource may be governed by a license agreement which restricts use to the European University Institute community. Each user is responsible for limiting use to individual, non-commercial purposes, without systematically downloading, distributing, or retaining substantial portions of information, provided that all copyright and other proprietary notices contained on the materials are retained. The use of software, including scripts, agents, or robots, is generally prohibited and may result in the loss of access to these resources for the entire European University Institute community
Isbn
9781461461340
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia.
Media type code
  • c
Other control number
10.1007/978-1-4614-6134-0
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(OCoLC)1011843166
Label
Empirical Agent-Based Modelling - Challenges and Solutions : Volume 1, The Characterisation and Parameterisation of Empirical Agent-Based Models, edited by Alexander Smajgl, Olivier Barreteau, (electronic resource)
Link
https://eui.idm.oclc.org/login?url=http://dx.doi.org/10.1007/978-1-4614-6134-0
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier.
Color
not applicable
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent.
Contents
Empiricism and agent-based modelling -- A case study on characterising and parameterising an agent-based integrated model of recreational fishing and coral reef ecosystem dynamics -- An Agent-Based Model of Tourist Movements in New Zealand -- Human--ecosystem interaction in large ensemble model systems -- Using Spatially Explicit Marketing Data to Build Social Simulations
Control code
978-1-4614-6134-0
Dimensions
unknown
Extent
XIII, 249 pages 30 illustrations, 20 illustrations in color.
File format
multiple file formats
Form of item
electronic
Governing access note
Use of this electronic resource may be governed by a license agreement which restricts use to the European University Institute community. Each user is responsible for limiting use to individual, non-commercial purposes, without systematically downloading, distributing, or retaining substantial portions of information, provided that all copyright and other proprietary notices contained on the materials are retained. The use of software, including scripts, agents, or robots, is generally prohibited and may result in the loss of access to these resources for the entire European University Institute community
Isbn
9781461461340
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia.
Media type code
  • c
Other control number
10.1007/978-1-4614-6134-0
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(OCoLC)1011843166

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