Autonomous development of goals: From generic rewards to goal and self detection

DOI

Description

Goals are abstractions that express agents’ intention and allow them to organize their behavior appropriately. How can agents develop such goals autonomously? This paper proposes a conceptual and computational account to this longstanding problem. We argue to consider goals as abstractions of lowerlevel intention mechanisms such as rewards and values, and point out that goals need to be considered alongside with a detection of the own actions’ effects. Then, both goals and self-detection can be learned from generic rewards. We show experimentally that task-unspecific rewards induced by visual saliency lead to self and goal representations that constitute goal-directed reaching.

Journal

Details 詳細情報について

Report a problem

Back to top