This chapter studies the bidirectional causal interactions between curiosity and learning and
discusses how understanding these interactions can be leveraged in educational …

Curiosity is a core driver for life‐long learning, problem‐solving and decision‐making. In a
broad sense, curiosity is defined as the intrinsically motivated acquisition of novel …

A comprehensive overview of an interdisciplinary approach to robotics that takes direct
inspiration from the developmental and learning phenomena observed in children's …

Recent years have seen a considerable surge of research on interest-based engagement,
examining how and why people are engaged in activities without relying on extrinsic …

Curiosity-driven learning is foundational to human cognition. By enabling humans to
autonomously decide when and what to learn, curiosity has been argued to be crucial for …

The objective of a reinforcement learning agent is to behave so as to maximise the sum of a
suitable scalar function of state: the reward. These rewards are typically given and …

In this paper, we present goal-discovering robotic architecture for intrisically-motivated
learning (GRAIL), a four-level architecture that is able to autonomously: 1) discover changes …

Devising efficient strategies for exploration in large open-ended spaces is one of the most
difficult computational problems of intelligent organisms. Because the available rewards are …

Although the spontaneous origins of concepts from interaction is often given for granted,
how the process can start without a fully developed sensorimotor representation system has …

As more and more AI agents are used in practice, it is time to think about how to make these
agents fully autonomous so that they can (1) learn by themselves continually in a self …