Abstract (may include machine translation)
Routing is an essential process for pedestrian Agent-Based Modelling (ABM). ABM is a computational tool to model and analyse human behaviour. The process of routing is well-studied in both Computer Science and Cognitive Science. However, routing in ABM is often taken for granted and both its impact and its implementation are disregarded. In this work, I unpack the blackbox of routing in ABM and take insights from Cognitive Science to improve the realism of routing.
In particular, I focus on the agent’s mental representation of the environment and
typical errors in encoding this information. I propose to deviate from classical Computer Science paradigm of optimality to capture human behaviour more accurately. The resulting model produces routes that are less prone to typical computational artefacts such as ziggzagging, i. e. turning more often than humans would, and bottlenecks, i. e. always routing through one particular node because it is minimally more efficient.
In particular, I focus on the agent’s mental representation of the environment and
typical errors in encoding this information. I propose to deviate from classical Computer Science paradigm of optimality to capture human behaviour more accurately. The resulting model produces routes that are less prone to typical computational artefacts such as ziggzagging, i. e. turning more often than humans would, and bottlenecks, i. e. always routing through one particular node because it is minimally more efficient.
| Original language | English |
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| Qualification | Master of Science |
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| Publisher | |
| DOIs | |
| State | Published - 2018 |
| Externally published | Yes |