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1
Reinforcement Learning with Parameterized Actions
We introduce a model-free algorithm for learning in Markov decision processes with parameterized actions—discrete actions with …
Warwick Masson
,
Pravesh Ranchod
,
George Konidaris
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Autonomous Prediction of Performance-based Standards for Heavy Vehicles
In this paper we use content-based features to perform automatic classification of music pieces into genres. We categorise these …
Robert Berman
,
Richardt Benade
,
Benjamin Rosman
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Single-labelled Music Genre Classification Using Content-Based Features
In this paper we use content-based features to perform automatic classification of music pieces into genres. We categorise these …
Ritesh Ajoodha
,
Richard Klein
,
Benjamin Rosman
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Knowledge Transfer for Learning Robot Models via Local Procrustes Analysis
Learning of robot kinematic and dynamic models from data has attracted much interest recently as an alternative to manually defined …
Ndivhuwo Makondo
,
Benjamin Rosman
,
Osamu Hasegawa
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Nonparametric Bayesian Reward Segmentation for Skill Discovery Using Inverse Reinforcement Learning
We present a method for segmenting a set of unstructured demonstration trajectories to discover reusable skills using inverse …
Pravesh Ranchod
,
Benjamin Rosman
,
George Konidaris
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Project
Enhancing Agent Safety through Autonomous Environment Adaptation
Exploration and self-directed learning are valuable components of early childhood development. This often comes at an unacceptable …
Benjamin Rosman
,
Bradley Hayes
,
Brian Scassellati
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CHAMP: A Bespoke Integrated System for Mobile Manipulation
Mobile manipulation is a robotics paradigm with the potential to make major contributions to a number of important domain areas. …
Beatrice van Eden
,
Benjamin Rosman
,
Daniel Withey
,
Terence Ratshidaho
,
Mogomotsi Keaikitse
,
Ditebogo Masha
,
Ashley Kleinhans
,
Ahmed Shaik
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Context-based Online Policy Instantiation for Multiple Tasks and Changing Environments
This paper addresses the problem of online decision making in continually changing and complex environments, with inherent …
Benjamin Rosman
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Feature Selection for Domain Knowledge Representation through Multitask Learning
Representation learning is a difficult and important problem for autonomous agents. This paper presents an approach to automatic …
Benjamin Rosman
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Giving Advice to Agents with Hidden Goals
This paper considers the problem of providing advice to an autonomous agent when neither the behavioural policy nor the goals of that …
Benjamin Rosman
,
Subramanian Ramamoorthy
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