Výsledky vyhledávání - "Ávila, Héctor"

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Task Modifiers for HTN Planning and Acting

Autor: Yuan, Weihang, Munoz-Avila, Hector, Gogineni, Venkatsampath Raja, Kondrakunta, Sravya, Cox, Michael, He, Lifang

The ability of an agent to change its objectives in response to unexpected events is desirable in dynamic environments. In order to provide this capability to hierarchical task network (HTN) planning, we propose an extension of the paradigm called ta

Externí odkaz: http://arxiv.org/abs/2202.04611

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Distributed Map Classification using Local Observations

Autor: Liu, Guangyi, Amini, Arash, Takáč, Martin, Muñoz-Avila, Héctor, Motee, Nader

We consider the problem of classifying a map using a team of communicating robots. It is assumed that all robots have localized visual sensing capabilities and can exchange their information with neighboring robots. Using a graph decomposition techni

Externí odkaz: http://arxiv.org/abs/2012.10480

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Hierarchical Reinforcement Learning for Deep Goal Reasoning: An Expressiveness Analysis

Autor: Yuan, Weihang, Muñoz-Avila, Héctor

Hierarchical DQN (h-DQN) is a two-level architecture of feedforward neural networks where the meta level selects goals and the lower level takes actions to achieve the goals. We show tasks that cannot be solved by h-DQN, exemplifying the limitation o

Externí odkaz: http://arxiv.org/abs/2006.11704

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A Layered Architecture for Active Perception: Image Classification using Deep Reinforcement Learning

Autor: Mousavi, Hossein K., Liu, Guangyi, Yuan, Weihang, Takáč, Martin, Muñoz-Avila, Héctor, Motee, Nader

We propose a planning and perception mechanism for a robot (agent), that can only observe the underlying environment partially, in order to solve an image classification problem. A three-layer architecture is suggested that consists of a meta-layer t

Externí odkaz: http://arxiv.org/abs/1909.09705

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