Silva Simões, Lucas;
(2023)
Normative studies of single-event memories and multitask decision-making.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
In recent decades, there have been significant advancements in the study of cognition and behaviour, with various aspects of memory, learning, and decision-making being characterised and analysed. One important approach in this endeavour is computational modelling, which allows researchers to explore the normative mechanisms underlying cognitive phenomena. This thesis is situated within this line of research, and investigates the normative principles governing two aspects of cognition and behaviour: the appropriateness of single-event memories and optimal decision-making in multi-task environments. Single-event memories are a typical aspect of human life but stand in contrast to common practice in machine learning, where it is better to condense information from several experiences into a set of statistics for robust and generalisable representations. In the first part of this thesis, we build on past research and postulate that single-event memories can support common statistical learning approaches. We provide analytical calculations and simulations to demonstrate that this cannot entirely account for the existence of single-event memories in the human brain. The second part of the thesis examines the fact that humans and other animals have multiple decisions to make in a day and can decide to move from one to the other at will. While it is understood that they do this to maximise rewards such as food, social validation, and pleasure, current models at times fail to explain behaviour observed in the lab. We use ideas from foraging theory and reinforcement learning to study optimal behaviour in this problem, first in static environments, then in dynamic ones.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Normative studies of single-event memories and multitask decision-making |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2023. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Gatsby Computational Neurosci Unit |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10181389 |
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