Getting stuck in a rut as an emergent feature of a dynamic decision-making system
Human sensorimotor decision making has a tendency to get ‘stuck in a rut’, being biased towards selecting a previously implemented action structure (hysteresis). Existing explanations propose this is the consequence of an agent efficiently modifying an existing plan, rather than creating a new plan...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
The Royal Society
2024-04-01
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| Series: | Royal Society Open Science |
| Subjects: | |
| Online Access: | https://royalsocietypublishing.org/doi/10.1098/rsos.231550 |
| _version_ | 1827249721496829952 |
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| author | Matthew Warburton Jack Brookes Mohamed Hasan Matteo Leonetti Mehmet Dogar He Wang Anthony G. Cohn Faisal Mushtaq Mark Mon-Williams |
| author_facet | Matthew Warburton Jack Brookes Mohamed Hasan Matteo Leonetti Mehmet Dogar He Wang Anthony G. Cohn Faisal Mushtaq Mark Mon-Williams |
| author_sort | Matthew Warburton |
| collection | DOAJ |
| description | Human sensorimotor decision making has a tendency to get ‘stuck in a rut’, being biased towards selecting a previously implemented action structure (hysteresis). Existing explanations propose this is the consequence of an agent efficiently modifying an existing plan, rather than creating a new plan from scratch. Instead, we propose that hysteresis is an emergent property of a system learning from the consequences of its actions. To examine this, 152 participants moved a cursor to a target on a tablet device while avoiding an obstacle. Hysteresis was observed when the obstacle moved sequentially across the screen between trials, whereby the participant continued moving around the same side of the obstacle despite it now requiring a larger movement than the alternative. Two further experiments (n = 20) showed an attenuation when time and resource constraints were eased. We created a simple computational model capturing probabilistic estimate updating that showed the same patterns of results. This provides, to our knowledge, the first computational demonstration of how sensorimotor decision making can get ‘stuck in a rut’ through the updating of the probability estimates associated with actions. |
| first_indexed | 2024-04-24T13:58:52Z |
| format | Article |
| id | doaj.art-5688c05aa7914ea6af73d114a36b6037 |
| institution | Directory Open Access Journal |
| issn | 2054-5703 |
| language | English |
| last_indexed | 2025-03-21T23:52:09Z |
| publishDate | 2024-04-01 |
| publisher | The Royal Society |
| record_format | Article |
| series | Royal Society Open Science |
| spelling | doaj.art-5688c05aa7914ea6af73d114a36b60372024-05-17T20:02:35ZengThe Royal SocietyRoyal Society Open Science2054-57032024-04-0111410.1098/rsos.231550Getting stuck in a rut as an emergent feature of a dynamic decision-making systemMatthew Warburton0Jack Brookes1Mohamed Hasan2Matteo Leonetti3Mehmet Dogar4He Wang5Anthony G. Cohn6Faisal Mushtaq7Mark Mon-Williams8School of Psychology, University of Leeds , Leeds, UKSchool of Psychology, University of Leeds , Leeds, UKSchool of Computing, University of Leeds , Leeds, UKSchool of Computing, University of Leeds , Leeds, UKSchool of Computing, University of Leeds , Leeds, UKSchool of Computing, University of Leeds , Leeds, UKSchool of Computing, University of Leeds , Leeds, UKSchool of Psychology, University of Leeds , Leeds, UKSchool of Psychology, University of Leeds , Leeds, UKHuman sensorimotor decision making has a tendency to get ‘stuck in a rut’, being biased towards selecting a previously implemented action structure (hysteresis). Existing explanations propose this is the consequence of an agent efficiently modifying an existing plan, rather than creating a new plan from scratch. Instead, we propose that hysteresis is an emergent property of a system learning from the consequences of its actions. To examine this, 152 participants moved a cursor to a target on a tablet device while avoiding an obstacle. Hysteresis was observed when the obstacle moved sequentially across the screen between trials, whereby the participant continued moving around the same side of the obstacle despite it now requiring a larger movement than the alternative. Two further experiments (n = 20) showed an attenuation when time and resource constraints were eased. We created a simple computational model capturing probabilistic estimate updating that showed the same patterns of results. This provides, to our knowledge, the first computational demonstration of how sensorimotor decision making can get ‘stuck in a rut’ through the updating of the probability estimates associated with actions.https://royalsocietypublishing.org/doi/10.1098/rsos.231550decision-makinghysteresischoice bias |
| spellingShingle | Matthew Warburton Jack Brookes Mohamed Hasan Matteo Leonetti Mehmet Dogar He Wang Anthony G. Cohn Faisal Mushtaq Mark Mon-Williams Getting stuck in a rut as an emergent feature of a dynamic decision-making system Royal Society Open Science decision-making hysteresis choice bias |
| title | Getting stuck in a rut as an emergent feature of a dynamic decision-making system |
| title_full | Getting stuck in a rut as an emergent feature of a dynamic decision-making system |
| title_fullStr | Getting stuck in a rut as an emergent feature of a dynamic decision-making system |
| title_full_unstemmed | Getting stuck in a rut as an emergent feature of a dynamic decision-making system |
| title_short | Getting stuck in a rut as an emergent feature of a dynamic decision-making system |
| title_sort | getting stuck in a rut as an emergent feature of a dynamic decision making system |
| topic | decision-making hysteresis choice bias |
| url | https://royalsocietypublishing.org/doi/10.1098/rsos.231550 |
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