The dominant motivational paradigm in embodied AI so far is based on the classical behaviorist approach of reward and punishment. The paper introduces a new principle based on ’flow theory’. This new, ‘autotelic’, principle proposes that agents can become self-motivated if their target is to balance challenges and skills. The paper presents an operational version of this principle and argues that it enables a developing robot to self-regulate its development.Peer reviewe
International audienceBuilding autonomous machines that can explore open-ended environments, discove...
A large part of current research into autonomous control is concerned with building agents that can ...
This article was supported by the German Research Foundation (DFG) and the Open Access Publication F...
Abstract In this paper, we describe our design of a behaviour-based control system for autonomous ag...
Motivation is a central concept in the development of autonomous agents and robots. This paper descr...
This paper explores a philosophy and connectionist algorithm for creating a long-term, self-motivate...
This paper explores a philosophy and connectionist algorithm for creating a long-term, self-motivate...
This thesis studies the role of intrinsic motivation in the emergence and development of communicati...
AI agents are becoming significantly more general and autonomous. We argue for the “Reward Engineeri...
In this paper we describe an intrinsic developmental algorithm designed to allow a mobile robot to ...
This paper describes a method for designing robots to learn self-motivated behaviors rather than ext...
Autonomous acquisition of many different skills is neces- sary to foster behavioural versatility in ...
This paper explores a philosophy and connectionist al- gorithm for creating a long-term, self-organi...
We propose an intrinsic developmental algorithm that is designed to allow a mobile robot to incremen...
What dynamics can enable a robot to continuously develop new visual know-how? We present a rst exper...
International audienceBuilding autonomous machines that can explore open-ended environments, discove...
A large part of current research into autonomous control is concerned with building agents that can ...
This article was supported by the German Research Foundation (DFG) and the Open Access Publication F...
Abstract In this paper, we describe our design of a behaviour-based control system for autonomous ag...
Motivation is a central concept in the development of autonomous agents and robots. This paper descr...
This paper explores a philosophy and connectionist algorithm for creating a long-term, self-motivate...
This paper explores a philosophy and connectionist algorithm for creating a long-term, self-motivate...
This thesis studies the role of intrinsic motivation in the emergence and development of communicati...
AI agents are becoming significantly more general and autonomous. We argue for the “Reward Engineeri...
In this paper we describe an intrinsic developmental algorithm designed to allow a mobile robot to ...
This paper describes a method for designing robots to learn self-motivated behaviors rather than ext...
Autonomous acquisition of many different skills is neces- sary to foster behavioural versatility in ...
This paper explores a philosophy and connectionist al- gorithm for creating a long-term, self-organi...
We propose an intrinsic developmental algorithm that is designed to allow a mobile robot to incremen...
What dynamics can enable a robot to continuously develop new visual know-how? We present a rst exper...
International audienceBuilding autonomous machines that can explore open-ended environments, discove...
A large part of current research into autonomous control is concerned with building agents that can ...
This article was supported by the German Research Foundation (DFG) and the Open Access Publication F...