We present an algorithm, HI-MAT (Hierarchy Induction via Models And Trajectories), that discovers MAXQ task hierarchies by applying dynamic Bayesian network models to a successful...
We propose a data structure that decreases complexity of unsupervised competitive learning algorithms which are based on the growing cells structures approach. The idea is based on...
— This paper describes a general approach for the unsupervised learning of behaviors in a behavior-based robot. The key idea is to formalize a behavior produced by a Motor Map dr...
Paolo Arena, Luigi Fortuna, Mattia Frasca, Luca Pa...
Reinforcement Learning is commonly used for learning tasks in robotics, however, traditional algorithms can take very long training times. Reward shaping has been recently used to ...
Ana C. Tenorio-Gonzalez, Eduardo F. Morales, Luis ...
We discuss vision as a sensory modality for systems that effect actions in response to perceptions. While the internal representations informed by vision may be arbitrarily compl...