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1
A Boolean Task Algebra for Reinforcement Learning
The ability to compose learned skills to solve new tasks is an important property for lifelong-learning agents. In this work we …
Geraud Nangue Tasse
,
Steven James
,
Benjamin Rosman
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Project
Utilising Uncertainty for Efficient Learning of Likely-Admissible Heuristics
Likely-admissible heuristics have previously been introduced as heuristics that are admissible with some probability. While such …
Ofir Marom
,
Benjamin Rosman
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Supplementary Material
Discovery of Influence between Processes Represented by Hidden Markov Models
Learning the underlying structure between processes is a common problem found in the sciences, however not much work is dedicated …
Ritesh Ajoodha
,
Benjamin Rosman
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Learning Portable Representations for High-Level Planning
We present a framework for autonomously learning a portable representation that describes a collection of low-level continuous …
Steven James
,
Benjamin Rosman
,
George Konidaris
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Project
Combining Primitive DQNs for Improved Reinforcement Learning in Minecraft
We ask whether a reinforcement learning agent learns better by first learning the skills to perform smaller tasks in a complex …
Matthew Reynard
,
Herman Kamper
,
Herman A Engelbrecht
,
Benjamin Rosman
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Confident in the Crowd: Bayesian Inference to Improve Data Labelling in Crowdsourcing
With the increased interest in machine learning and big data problems, the need for large amounts of labelled data has also grown. …
Pierce Burke
,
Richard Klein
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Inter-and Intra-domain Knowledge Transfer for Related Tasks in Deep Character Recognition
Pre-training a deep neural network on the ImageNet dataset is a common practice for training deep learning models, and generally yields …
Nishai Kooverjee
,
Steven James
,
Terence Van Zyl
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Learning Options from Demonstration using Skill Segmentation
We present a method for learning options from segmented demonstration trajectories. The trajectories are first segmented into skills …
Matthew Cockcroft
,
Shahil Mawjee
,
Steven James
,
Pravesh Ranchod
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Project
Quantisation and Pruning for Neural Network Compression and Regularisation
Deep neural networks are typically too computationally expensive to run in real-time on consumer-grade hardware and low-powered …
Kimessha Paupamah
,
Steven James
,
Richard Klein
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Sentiment Analysis as an Indicator to Evaluate Gender disparity on Sexual Violence Tweets in South Africa
South Africa has one of the highest rates of sexual violence in the world, and with this technology era being the information age, it …
Jude Oyasor
,
Mpho Raborife
,
Pravesh Ranchod
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