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      Exploring the role of spatial cognition in predicting urban traffic flow through agent-based modelling

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      Transportation Research Part A: Policy and Practice
      Elsevier BV

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          Most cited references54

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          Path integration and the neural basis of the 'cognitive map'.

          The hippocampal formation can encode relative spatial location, without reference to external cues, by the integration of linear and angular self-motion (path integration). Theoretical studies, in conjunction with recent empirical discoveries, suggest that the medial entorhinal cortex (MEC) might perform some of the essential underlying computations by means of a unique, periodic synaptic matrix that could be self-organized in early development through a simple, symmetry-breaking operation. The scale at which space is represented increases systematically along the dorsoventral axis in both the hippocampus and the MEC, apparently because of systematic variation in the gain of a movement-speed signal. Convergence of spatially periodic input at multiple scales, from so-called grid cells in the entorhinal cortex, might result in non-periodic spatial firing patterns (place fields) in the hippocampus.
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            Cognitive maps in rats and men.

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              Agent-based modeling: methods and techniques for simulating human systems.

              E Bonabeau (2002)
              Agent-based modeling is a powerful simulation modeling technique that has seen a number of applications in the last few years, including applications to real-world business problems. After the basic principles of agent-based simulation are briefly introduced, its four areas of application are discussed by using real-world applications: flow simulation, organizational simulation, market simulation, and diffusion simulation. For each category, one or several business applications are described and analyzed.
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                Author and article information

                Contributors
                Journal
                Transportation Research Part A: Policy and Practice
                Transportation Research Part A: Policy and Practice
                Elsevier BV
                09658564
                March 2018
                March 2018
                : 109
                : 14-23
                Article
                10.1016/j.tra.2018.01.020
                cece3096-078f-40e9-ac96-9985a56cec68
                © 2018

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by/4.0/

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