This paper addresses agents' intentions as building blocks of imitation learning that abstract local situations of the agent, and proposes a hierarchical hidden Markov model ...
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
Nonlinear dendritic processing appears to be a feature of biological neurons and would also be of use in many applications of artificial neural networks. This paper presents a mod...
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
While several hierarchical classification methods have been applied to web content, such techniques invariably rely on a pre-defined taxonomy of documents. We propose a new techni...