Multi-agent models of spatial cognition, learning and complex choice behavior in urban environments

Theo Arentze; Harry Timmermans

doi:10.1007/3-540-29710-3_12

Multi-agent models of spatial cognition, learning and complex choice behavior in urban environments

Theo Arentze, Harry Timmermans

Urban Planning and Transportation

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

10 Citations (Scopus)

Abstract

This chapter provides an overview of ongoing research projects in the DDSS research program at TUE related to multi-agents. Projects include (a) the use of multi-agent models and concepts of artificial intelligence to develop models of activity-travel behavior; (b) the use of a multi-agent model to simulate pedestrian movement in urban environments; (c) the use of multi-agent models for simulating the dynamics of land development; (d) the use of multi-agent models to simulate learning and adaptation behavior in non-stationary urban environments and under conditions of uncertainty and information search and (e) the development of computational models linking cognition, choice set formation, activity travel behavior and land use dynamics. The scope, theoretical underpinnings and results of numerical and empirical simulations are presented.

Original language	English
Title of host publication	Complex Artificial Environments: Simulation, Cognition and VR in the Study and Planning of Cities
Editors	J. Portugali
Publisher	Springer
Pages	181-200
Number of pages	20
ISBN (Electronic)	978-3-540-29710-9
ISBN (Print)	9783540259176
DOIs	https://doi.org/10.1007/3-540-29710-3_12
Publication status	Published - 2006

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10.1007/3-540-29710-3_12

Cite this

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Multi-agent models of spatial cognition, learning and complex choice behavior in urban environments. / Arentze, Theo; Timmermans, Harry.
Complex Artificial Environments: Simulation, Cognition and VR in the Study and Planning of Cities. ed. / J. Portugali. Springer, 2006. p. 181-200.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

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Multi-agent models of spatial cognition, learning and complex choice behavior in urban environments

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