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Catching heuristics are optimal control policies

Belousov, Boris ; Neumann, Gerhard ; Rothkopf, Constantin A. ; Peters, Jan (2022)
Catching heuristics are optimal control policies.
Advances in Neural Information Processing Systems 29 (NIPS 2016). Barcelona, Spain (05.-10.12.2016)
doi: 10.26083/tuprints-00020556
Conference or Workshop Item, Secondary publication, Publisher's Version

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Item Type: Conference or Workshop Item
Type of entry: Secondary publication
Title: Catching heuristics are optimal control policies
Language: English
Date: 2022
Place of Publication: Darmstadt
Publisher: Neural Information Processing Systems
Book Title: Advances in Neural Information Processing Systems 29 : 30th Annual Conference on Neural Information Processing Systems 2016
Collation: 9 Seiten
Event Title: Advances in Neural Information Processing Systems 29 (NIPS 2016)
Event Location: Barcelona, Spain
Event Dates: 05.-10.12.2016
DOI: 10.26083/tuprints-00020556
Corresponding Links:
Origin: Secondary publication service

Two seemingly contradictory theories attempt to explain how humans move to intercept an airborne ball. One theory posits that humans predict the ball trajectory to optimally plan future actions; the other claims that, instead of performing such complicated computations, humans employ heuristics to reactively choose appro- priate actions based on immediate visual feedback. In this paper, we show that interception strategies appearing to be heuristics can be understood as computa- tional solutions to the optimal control problem faced by a ball-catching agent acting under uncertainty. Modeling catching as a continuous partially observable Markov decision process and employing stochastic optimal control theory, we discover that the four main heuristics described in the literature are optimal solutions if the catcher has sufficient time to continuously visually track the ball. Specifically, by varying model parameters such as noise, time to ground contact, and perceptual latency, we show that different strategies arise under different circumstances. The catcher’s policy switches between generating reactive and predictive behavior based on the ratio of system to observation noise and the ratio between reaction time and task duration. Thus, we provide a rational account of human ball-catching behavior and a unifying explanation for seemingly contradictory theories of target interception on the basis of stochastic optimal control.

Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-205568
Classification DDC: 000 Generalities, computers, information > 004 Computer science
100 Philosophy and psychology > 150 Psychology
Divisions: 20 Department of Computer Science > Intelligent Autonomous Systems
03 Department of Human Sciences > Institute for Psychology
TU-Projects: EC/H2020|640554|SKILLS4ROBOTS
Date Deposited: 18 Nov 2022 14:23
Last Modified: 24 Mar 2023 09:17
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/20556
PPN: 502453907
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