| Paper: | PS-1B.43 | ||
| Session: | Poster Session 1B | ||
| Location: | H Fläche 1.OG | ||
| Session Time: | Saturday, September 14, 16:30 - 19:30 | ||
| Presentation Time: | Saturday, September 14, 16:30 - 19:30 | ||
| Presentation: | Poster | ||
| Publication: | 2019 Conference on Cognitive Computational Neuroscience, 13-16 September 2019, Berlin, Germany | ||
| Paper Title: | Dynamic Integration of Forward Planning and Heuristic Preferences in a Sequential Two-Goal Task | ||
| Manuscript: | Click here to view manuscript | ||
| License: |  This work is licensed under a Creative Commons Attribution 3.0 Unported License. |
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| DOI: | https://doi.org/10.32470/CCN.2019.1034-0 | ||
| Authors: | Florian Ott, Dimitrije Markovic, Alexander Strobel, Stefan Kiebel, Technische Universität Dresden, Germany | ||
| Abstract: | To decide which goal to prioritize at what point in time, one has to evaluate the consequences of future actions by forward planning. However, when the goal is still temporally distant, detailed forward planning can be prohibitively costly. One way to select actions at minimal computational costs is to use heuristics. It is an open question how humans mix heuristics with forward planning to balance computational costs with goal reaching performance. To test a hypothesis about dy-namic mixing of heuristics with forward planning, we used a novel stochastic sequential two-goal task. We found that participants’ decisions substantially deviated from an optimal full planning agent at the early stages of goal-reaching sequences. Only towards the end of the sequence, participant’s behavior converged to near optimal performance. Subsequent model-based anal-yses showed that participants used heuristic prefer-ences when the goal was temporally distant and switched to forward planning, when the goal was close. | ||