Abstract
In this paper, we explore an approach for developing an initial agent population that is suitable for integrating two component agent based models, representing conceptually the same agents. For some models the structure of the initial population is an important aspect of the model. When integrating two (or more) models that represent the same agents, we require a single integrated agent population (or unique mappings between the two populations). Obtaining such is not straightforward if we wish to preserve important structural characteristics of the component populations. We describe here a methodology inspired by work in constructing synthetic populations which are structurally similar to a real population. The approach uses the Iterative Proportional Fitting Procedure (IPFP) to combine two different data sets in a way that preserves the structure of each. We apply our approach to a specific case study and evaluate the quality of the resulting integrated population.
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Notes
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We describe the procedure for two components, but multi-dimensional IPFP can be used for cases with three or four components.
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This is further discussed in Sect. 4.
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Exact adherence modulo rounding errors. We must of course round agent numbers obtained from percentages to be whole numbers.
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As mentioned, IPFP rounding introduces errors. We rounded by taking the floor values which gave populations of around 3% less than 4000. This choice is not critical for us, however for a detailed discussion of rounding issues, see [11].
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This research was funded in part by the Australian Research Council, SJB Urban and the (Melbourne) Metropolitan Planning Authority through Linkage Project grant LP130100008.
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Wickramasinghe, B.N., Singh, D., Padgham, L. (2017). Heuristic Data Merging for Constructing Initial Agent Populations. In: Sukthankar, G., Rodriguez-Aguilar, J. (eds) Autonomous Agents and Multiagent Systems. AAMAS 2017. Lecture Notes in Computer Science(), vol 10643. Springer, Cham. https://doi.org/10.1007/978-3-319-71679-4_12
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