Uncertainty quantification and exploration-exploitation trade-off in humans

The main objective of this paper is to outline a theoretical framework to analyse how humans' decision-making strategies under uncertainty manage the trade-off between information gathering (exploration) and reward seeking (exploitation). A key observation, motivating this line of research, is the awareness that human learners are amazingly fast and effective at adapting to unfamiliar environments and incorporating upcoming knowledge: this is an intriguing behaviour for cognitive sciences as well as an important challenge for Machine Learning... (read more)

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Methods used in the Paper

Graph Embeddings
Gaussian Process
Non-Parametric Classification