Titlebook: Empirical Agent-Based Modelling - Challenges and Solutions; Volume 1, The Charac Alexander Smajgl,Olivier Barreteau Book 2014 Springer Scie

腼腆

Using Spatially Explicit Marketing Data to Build Social Simulations,they rely on detailed data on cognitive and behavioural variables e.g. gathered through a domain-specific survey to craftspecific behavioural agent rules.However, both scales cannot easilybe connected. This chapter describes a method of using data stemming from geo-marketing research to support this

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Myocyte

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Parameterisation of Individual Working Dynamics, areas experience a rebirth, even in areas where until recently development was not considered possible. Our modelling effort aims at better understanding these heterogeneities. To deal with this objective, the modelling and the parameterisation should be strongly constraint by available data. This

江湖郎中

How to Characterise and Parameterise Agents in Electricity Market Simulation Models: The Case of Gees in a competitive electricity market. It focuses on adaptive behaviour of generation and investment companies in Australia’s National Electricity Market (NEM) as modelled by Genersys. Through initiatives such as formal focus group meetings, gathering observations of industry experts, analysing mar

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Building Empirical Multiagent Models from First Principles When Fieldwork Is Difficult or Impossiblimpossible to conduct and data is primarily of qualitative nature. Empirical multiagent models have become ever more popular over the last decade. While informing models using statistical and geospatial data can orient itself on more established techniques and standards, methodological challenges pe

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978-1-4939-5252-6Springer Science+Business Media New York 2014