Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
—In this paper, we study how a humanoid robot can learn affordance relations in his environment through its own interactions in an unsupervised way. Specifically, we developed a...
Baris Akgun, Nilgun Dag, Tahir Bilal, Ilkay Atil, ...
This work is about the relevance of Gibson’s concept of affordances [1] for visual perception in interactive and autonomous robotic systems. In extension to existing functional ...
Gerald Fritz, Lucas Paletta, Ralph Breithaupt, Eri...
In the single rent-to-buy decision problem, without a priori knowledge of the amount of time a resource will be used we need to decide when to buy the resource, given that we can ...
A novel model for dynamic emergence and adaptation of embodied behavior is proposed. A musculo-skeletal system is controlled by a number of chaotic elements, each of which driving...