The concept of "intrinsic motivation", initially proposed and developed within psychology, is gaining an increasing attention within cognitive sciences for its potential to produce open-ended learning machines and robots. However, a clear definition of the phenomenon is not yet available. This theoretical paper aims to clarify what intrinsic motivations are from a biological perspective. To this purpose, it first shows how intrinsic motivations can be defined contrasting them to extrinsic motivations from an evolutionary perspective: whereas extrinsic motivations guide learning of behaviours that directly increase fitness, intrinsic motivations drive the acquisition of knowledge and skills that contribute to produce behaviours that increase fitness only in a later stage. Given this difference, extrinsic motivations generate learning signals on the basis of events involving body homeostatic regulations, whereas intrinsic motivations generate learning signals based on events taking place within the brain itself. These ideas are supported by presenting some examples of biological mechanisms underlying the two types of motivations. The paper closes by linking the theory to the current major computational views on intrinsic motivations and by listing the main open issues of the field.
