title: Information-seeking, curiosity, and attention: computational and neural mechanisms.
abstract: Intelligent animals devote much time and energy to exploring and obtaining information, but the underlying mechanisms are poorly understood. We review recent developments on this topic that have emerged from the traditionally separate fields of machine learning, eye movements in natural behavior, and studies of curiosity in psychology and neuroscience. These studies show that exploration may be guided by a family of mechanisms that range from automatic biases toward novelty or surprise to systematic searches for learning progress and information gain in curiosity-driven behavior. In addition, eye movements reflect visual information searching in multiple conditions and are amenable for cellular-level investigations. This suggests that the oculomotor system is an excellent model system for understanding information-sampling mechanisms.
authors.affiliation: Department of Neuroscience, Columbia University, New York, NY, USA; Kavli Institute for Brain Science, Columbia University, New York, NY, USA. Electronic address: jg2141@columbia.edu.
authors.forename: Jacqueline
authors.initials: J
authors.lastname: Gottlieb
authors.forename: Pierre-Yves
authors.initials: PY
authors.lastname: Oudeyer
authors.forename: Manuel
authors.initials: M
authors.lastname: Lopes
authors.forename: Adrien
authors.initials: A
authors.lastname: Baranes
mesh_terms: D000818:Animals; D001185:Artificial Intelligence; D001288:Attention / Q000502:physiology*; D001921:Brain / Q000502:physiology*; D005106:Exploratory Behavior / Q000502:physiology*; D006801:Humans; D057226:Information Seeking Behavior / Q000502:physiology*