Analyzing Strong Spatial Cognition: A Modeling Approach

Ven, Jasper van de; Fukuda, Munehiro; Schultheis, Holger; Freksa, Christian; Barkowsky, Thomas

doi:10.1007/978-3-319-96385-3_14

Cited by 3 publications

(2 citation statements)

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“…External scaffolding strategies have been shown to occur particularly often while performing spatial tasks (Wilson, 2002). Minimizing the computational effort by using properties of the spatial environment to facilitate one's actions is also consistent with behavioral strategies based on strong spatial cognition, that is, solving spatial problems by using physical manipulation and perception instead of formal computation processes (Freksa, 2015;van de Ven, Fukuda, Schultheis, Freksa, & Barkowsky, 2018). Strong spatial cognition relies on object affordances to complement the knowledge level of problem solving in spatial domains, for example, when finding the shortest path between two nodes.…”

Section: Preferences In Spatial Cognitionmentioning

confidence: 68%

“…Consistent with previous work indicating that the spatial environment is often used to facilitate task performance, that is, intelligent use of space (Kirsh, 1995), external scaffolding (Clark, 1996;Wilson, 2002), strong spatial cognition (Freksa, 2015;van de Ven et al, 2018), and mental representation of space , we assume that human planning strategies during everyday tasks take spatial properties of the environment into account. As physical and cognitive effort are generally considered aversive (Hull, 1943;Kool et al, 2010) and stepwise-optimal strategies are preferred over planning ahead (Meder et al, 2019), we propose that humans prefer specific action orderings that take these preferences into account.…”

Section: The Opportunistic Planning Modelmentioning

confidence: 92%

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Action Selection in Everyday Activities: The Opportunistic Planning Model

Wenzl,

Schultheis

2024

Cognitive Science

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While action selection strategies in well‐defined domains have received considerable attention, little is yet known about how people choose what to do next in ill‐defined tasks. In this contribution, we shed light on this issue by considering everyday tasks, which in many cases have a multitude of possible solutions (e.g., it does not matter in which order the items are brought to the table when setting a table) and are thus categorized as ill‐defined problems. Even if there are no hard constraints on the ordering of subtasks in everyday activities, our research shows that people exhibit specific preferences. We propose that these preferences arise from bounded rationality, that is, people only have limited knowledge and processing power available, which results in a preference to minimize the overall physical and cognitive effort. In the context of everyday activities, this can be achieved by (a) taking properties of the spatial environment into account to use them to one's advantage, and (b) employing a stepwise‐optimal action selection strategy. We present the Opportunistic Planning Model as an explanatory cognitive model, which instantiates these assumptions, and show that the model is able to generalize to new everyday tasks, outperforming machine learning models such as neural networks during generalization.

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Section: Preferences In Spatial Cognitionmentioning

confidence: 68%