Add to ORKGAbstract. We present here a simulated model of a mobile Kuka Youbot which makes use of Dynamic Field Theory for its underlying perceptual and motor con-trol systems, while learning behavioral sequences through Reinforcement Learn-ing. Although dynamic neural fields have previously been used for robust control in robotics, high-level behavior has generally been pre-programmed by hand. In the present work we extend a recent framework for integrating reinforcement learning and dynamic neural fields, by using the principle of shaping, in order to reduce the search space of the learning agent
Although behaviour-based robotics has been successfully used to develop autonomous mobile robots up ...
Abstract — In this paper, we introduce a neural-dynamic architecture that enables autonomous learn-i...
In order to proceed along an action sequence, an autonomous agent has to recognize that the intended...
Abstract—A core requirement for autonomous robotic agents is that they be able to initiate actions t...
†Joint first authors. Abstract — We introduce a dynamic neural algorithm called Dynamic Neural (DN) ...
The implementation of sequence learning in robotic platforms offers several challenges. Deciding whe...
International audienceWithin this paper, a new kind of learning agents - so-called Constraint based ...
In the ¯eld of machine learning, reinforcement learning constitutes the idea of enabling machines to...
Behaviour based navigation frameworks present the need of mechanisms for behaviour coordination. Alg...
Learning plays a vital role in the development of situated agents. In this paper, we explore the use...
In this paper, we present an approach for combining reinforcement learning, learning by imitation, a...
In order to proceed along an action sequence, an autonomous agent has to recognize that the intended...
Animal’s rhythmic movements such as locomotion are considered to be controlled by neural circuits ca...
One of the major challenges in action generation for robotics and in the understanding of human moto...
Abstract—How sequences of actions are learned, remembered, and generated is a core problem of cognit...
Although behaviour-based robotics has been successfully used to develop autonomous mobile robots up ...
Abstract — In this paper, we introduce a neural-dynamic architecture that enables autonomous learn-i...
In order to proceed along an action sequence, an autonomous agent has to recognize that the intended...
Abstract—A core requirement for autonomous robotic agents is that they be able to initiate actions t...
†Joint first authors. Abstract — We introduce a dynamic neural algorithm called Dynamic Neural (DN) ...
The implementation of sequence learning in robotic platforms offers several challenges. Deciding whe...
International audienceWithin this paper, a new kind of learning agents - so-called Constraint based ...
In the ¯eld of machine learning, reinforcement learning constitutes the idea of enabling machines to...
Behaviour based navigation frameworks present the need of mechanisms for behaviour coordination. Alg...
Learning plays a vital role in the development of situated agents. In this paper, we explore the use...
In this paper, we present an approach for combining reinforcement learning, learning by imitation, a...
In order to proceed along an action sequence, an autonomous agent has to recognize that the intended...
Animal’s rhythmic movements such as locomotion are considered to be controlled by neural circuits ca...
One of the major challenges in action generation for robotics and in the understanding of human moto...
Abstract—How sequences of actions are learned, remembered, and generated is a core problem of cognit...
Although behaviour-based robotics has been successfully used to develop autonomous mobile robots up ...
Abstract — In this paper, we introduce a neural-dynamic architecture that enables autonomous learn-i...
In order to proceed along an action sequence, an autonomous agent has to recognize that the intended...