Resource-rational cognitive modelling : an information-theoretic approach

Abstract

How do humans coordinate perception and memory when learning and making decisions? Additionally, how do cognitive limitations and behavioural goals influence the optimal functioning of these faculties? Many accounts have sought to explain one or more of these faculties and how they impact behaviour. Relatively little attention has been given to how these cognitive faculties and goals are interrelated. This thesis will provide an account for how the human mind might optimally coordinate perception and memory with learning and decision making, relative to individual cognitive constraints. To achieve this goal, this thesis presents a cognitive model inspired by two areas of research. Firstly, computational modelling of biological visual perception and memory, which seeks to understand and predict these cognitive functions. Secondly, resource-rational analysis which seeks to understand how cognitive agents behave optimally under cognitive constraints, specifically information-theoretic constraints. The result of these connections is a cognitive model that makes predictions of perception, memory, learning, and decision making, while explaining how individuals coordinate these faculties relative to their goals and limitations. This model is first applied onto predicting human behaviour in a visual learning task collected in a previous experiment. Next, two novel experiments are introduced that incorporate utility judgements, change detection, and learning. Results from these experiments demonstrate that the proposed model is better able to account for detailed aspects of human behaviour compared to related methods. This improvement is due to the successful integration of multiple areas of research in biological perception and memory with learning and decision making, all under the resource-rational approach to cognitive modelling. This thesis concludes with a broad discussion of the importance of the proposed model and how it relates to remaining open questions in computational models of biological perception, memory, learning, and decision making.