Modeling learning and evolutionary adaptation processes in activity settings : theory and numerical simulations

H.J.P. Timmermans; T.A. Arentze; C.H. Joh

doi:10.3141/1718-04

Modeling learning and evolutionary adaptation processes in activity settings : theory and numerical simulations

H.J.P. Timmermans, T.A. Arentze, C.H. Joh

Urban Planning and Transportation

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Abstract

The development of a conceptual framework to build a model of multi-faceted choices underlying activity behavior is described. The conceptual framework views individuals developing stereotype behavior or scripts over time by learning. Various principles of learning as a function of state-dependent variables and as a function of latent behavior and adjustment principles are developed and formalized. The focus is on modeling long-term dynamics in activity choice heuristics. Theory, illustrated by a set of numerical experiments, is developed

Original language	English
Pages (from-to)	27-33
Journal	Transportation Research Record
Volume	1718
DOIs	https://doi.org/10.3141/1718-04
Publication status	Published - 2000

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title = "Modeling learning and evolutionary adaptation processes in activity settings : theory and numerical simulations",

abstract = "The development of a conceptual framework to build a model of multi-faceted choices underlying activity behavior is described. The conceptual framework views individuals developing stereotype behavior or scripts over time by learning. Various principles of learning as a function of state-dependent variables and as a function of latent behavior and adjustment principles are developed and formalized. The focus is on modeling long-term dynamics in activity choice heuristics. Theory, illustrated by a set of numerical experiments, is developed",

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AU - Timmermans, H.J.P.

AU - Arentze, T.A.

AU - Joh, C.H.

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AB - The development of a conceptual framework to build a model of multi-faceted choices underlying activity behavior is described. The conceptual framework views individuals developing stereotype behavior or scripts over time by learning. Various principles of learning as a function of state-dependent variables and as a function of latent behavior and adjustment principles are developed and formalized. The focus is on modeling long-term dynamics in activity choice heuristics. Theory, illustrated by a set of numerical experiments, is developed

U2 - 10.3141/1718-04

DO - 10.3141/1718-04

M3 - Article

SN - 0361-1981

VL - 1718

SP - 27

EP - 33

JO - Transportation Research Record

JF - Transportation Research Record

ER -

Modeling learning and evolutionary adaptation processes in activity settings : theory and numerical simulations

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