This paper reviews exploration techniques in deep reinforcement learning. Exploration
techniques are of primary importance when solving sparse reward problems. In sparse …

Attention is the important ability to flexibly control limited computational resources. It has
been studied in conjunction with many other topics in neuroscience and psychology …

A major shift is happening within neurophysiology: a population doctrine is drawing level
with the single-neuron doctrine that has long dominated the field. Population-level ideas …

Primates interact with the world by exploring visual objects; they seek opportunities to view
novel objects even when these have no extrinsic reward value. How the brain controls this …

Flexible decision-making requires animals to forego immediate rewards (exploitation) and
try novel choice options (exploration) to discover if they are preferable to familiar …

Notions of surprise and novelty have been used in various experimental and theoretical
studies across multiple brain areas and species. However,'surprise'and 'novelty'refer to …

Animals both explore and avoid novel objects in the environment, but the neural
mechanisms that underlie these behaviors and their dynamics remain uncharacterized …

Across the lifespan, individuals frequently choose between exploiting known rewarding
options or exploring unknown alternatives. A large body of work has suggested that children …

The detection of novel stimuli is critical to learn and survive in a dynamic environment.
Though novel stimuli powerfully affect brain activity, their impact on specific cell types and …

For many years, neuroscientists have investigated the behavioural, computational and
neurobiological mechanisms that support value-based decisions, revealing how humans …