ISER 2016: Experiments with hierarchical reinforcement learning of multiple grasping policies

ISER 2016: Experiments with hierarchical reinforcement learning of multiple grasping policies

Robotic grasping has attracted considerable interest, but it still remains a challenging task. The data-driven approach is a promising solution to the robotic grasping problem; this approach…

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ICRA 2017: Empowered Skills

ICRA 2017: Empowered Skills

Robot Reinforcement Learning (RL) algorithms return a policy that maximizes a global cumulative reward signal but typically do not create diverse behaviors. Hence, the policy…

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ICRA 2017: Layered Direct Policy Search for Learning Hierarchical Skills

ICRA 2017: Layered Direct Policy Search for Learning Hierarchical Skills

Solutions to real world robotic tasks often require complex behaviors in high dimensional continuous state and action spaces. Reinforcement Learning (RL) is aimed at learning…

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New RAL Paper: "Probabilistic Prioritization of Movement Primitives"

New RAL Paper: “Probabilistic Prioritization of Movement Primitives”

Alex’s last journal paper for his PhD has been accepted! Congratulations! A. Paraschos, R. Lioutikov, J. Peters, and G. Neumann, “Probabilistic prioritization of movement primitives,”…

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ICML 2016: Model-Free Trajectory Optimization for Reinforcement Learning

ICML 2016: Model-Free Trajectory Optimization for Reinforcement Learning

Many of the recent Trajectory Optimization algorithms alternate between local approximation of the dynamics and conservative policy update. However, linearly approximating the dynamics in order to derive…

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Learn-Cars: Structured Deep Learning for Autonomous Driving (UoL, 2017-2018, Toyota Europe)

Learn-Cars: Structured Deep Learning for Autonomous Driving (UoL, 2017-2018, Toyota Europe)

We will follow a data-driven approach to achieve human-like driving styles with human-level adaptability and personalization to the human driver/passenger. We will estimate driving controllers…

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Robo-Pick: Robots for Autonomous Mushroom Picking (UoL, 2017 - 2018, Innovate UK)

Robo-Pick: Robots for Autonomous Mushroom Picking (UoL, 2017 – 2018, Innovate UK)

This project aims to develop a new robotic picking system to harvest fresh mushrooms reducing labour demands by ca. 66%. The work will be carried…

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Machine Learning Journal 2016: Probabilistic inference for determining options in reinforcement learning

Machine Learning Journal 2016: Probabilistic inference for determining options in reinforcement learning

Tasks that require many sequential decisions or complex solutions are hard to solve using conventional reinforcement learning algorithms. Based on the semi Markov decision process…

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JMLR 2016: Hierarchical Relative Entropy Policy Search

JMLR 2016: Hierarchical Relative Entropy Policy Search

Many reinforcement learning (RL) tasks, especially in robotics, consist of multiple sub-tasks that are strongly structured. Such task structures can be exploited by incorporating hierarchical policies that…

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Artificial Intelligence Journal: Model-based contextual policy search for data-efficient generalization of robot skills

Artificial Intelligence Journal: Model-based contextual policy search for data-efficient generalization of robot skills

In robotics, lower-level controllers are typically used to make the robot solve a specific task in a fixed context. For example, the lower-level controller can…

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