Add to ORKGTraditionally, the task of developing a sensorimotor con-trol architecture for a situated autonomous robot was left to the human programmer of the robot. Prewiring robot behaviors by hand however becomes increasingl
Applications of learning to autonomous agents (simulated or real) have often been restricted to lear...
A fundamental challenge in robotics is controller design. While designing a robot\u27s individual be...
A Policy Gradient Reinforcement Learning (RL) technique is used to design the low level controllers ...
We describe an autonomous mobile robot that employs a simple sensorimotor learning algorithm at thre...
This paper describes a reinforcement connec-tionist learning mechanism that allows a goal-directed a...
Abstract. We describe an autonomous mobile robot that employs a simple sensorimotor learning algorít...
Autonomous Mobile Robots (AMR), to be truly flexible, should be equipped with learning capabilities,...
This paper presents an experimental investigation about Reinforcement Learning of multiple reactive ...
International Symposium on Industrial Electronics. Guimaraes, 7-11 July 1997.In this paper, an evolu...
We describe a robot system that autonomously acquires skills through interaction with its environmen...
. When dealing with autonomous robots, the definition of autonomy is important. Autonomous agents re...
We describe an autonomous mobile robot that employs a simple sensorimotor learning algoríthm at thre...
International audienceWithin the context of learning sequences of basic tasks to build a complex beh...
In this licenciate thesis, we discuss how to generate actions from percepts within an autonomous rob...
This paper adresses the identification of the key elements to be present in a generic, behaviour-bas...
Applications of learning to autonomous agents (simulated or real) have often been restricted to lear...
A fundamental challenge in robotics is controller design. While designing a robot\u27s individual be...
A Policy Gradient Reinforcement Learning (RL) technique is used to design the low level controllers ...
We describe an autonomous mobile robot that employs a simple sensorimotor learning algorithm at thre...
This paper describes a reinforcement connec-tionist learning mechanism that allows a goal-directed a...
Abstract. We describe an autonomous mobile robot that employs a simple sensorimotor learning algorít...
Autonomous Mobile Robots (AMR), to be truly flexible, should be equipped with learning capabilities,...
This paper presents an experimental investigation about Reinforcement Learning of multiple reactive ...
International Symposium on Industrial Electronics. Guimaraes, 7-11 July 1997.In this paper, an evolu...
We describe a robot system that autonomously acquires skills through interaction with its environmen...
. When dealing with autonomous robots, the definition of autonomy is important. Autonomous agents re...
We describe an autonomous mobile robot that employs a simple sensorimotor learning algoríthm at thre...
International audienceWithin the context of learning sequences of basic tasks to build a complex beh...
In this licenciate thesis, we discuss how to generate actions from percepts within an autonomous rob...
This paper adresses the identification of the key elements to be present in a generic, behaviour-bas...
Applications of learning to autonomous agents (simulated or real) have often been restricted to lear...
A fundamental challenge in robotics is controller design. While designing a robot\u27s individual be...
A Policy Gradient Reinforcement Learning (RL) technique is used to design the low level controllers ...