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06/01/2023
LLMatic: Neural Architecture Search via Large Language Models and Quality-Diversity Optimization
Large Language Models (LLMs) have emerged as powerful tools capable of a...
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05/31/2023
ROSARL: Reward-Only Safe Reinforcement Learning
An important problem in reinforcement learning is designing agents that ...
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02/03/2023
Hierarchically Composing Level Generators for the Creation of Complex Structures
Procedural content generation (PCG) is a growing field, with numerous ap...
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10/20/2022
Augmentative Topology Agents For Open-Ended Learning
In this work, we tackle the problem of open-ended learning by introducin...
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07/29/2022
Combining Evolutionary Search with Behaviour Cloning for Procedurally Generated Content
In this work, we consider the problem of procedural content generation f...
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06/23/2022
World Value Functions: Knowledge Representation for Learning and Planning
We propose world value functions (WVFs), a type of goal-oriented general...
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05/25/2022
Skill Machines: Temporal Logic Composition in Reinforcement Learning
A major challenge in reinforcement learning is specifying tasks in a man...
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05/18/2022
World Value Functions: Knowledge Representation for Multitask Reinforcement Learning
An open problem in artificial intelligence is how to learn and represent...
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05/12/2022
Accounting for the Sequential Nature of States to Learn Features for Reinforcement Learning
In this work, we investigate the properties of data that cause popular r...
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05/04/2022
Learning Abstract and Transferable Representations for Planning
We are concerned with the question of how an agent can acquire its own r...
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04/22/2022
Adaptive Online Value Function Approximation with Wavelets
Using function approximation to represent a value function is necessary ...
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04/18/2022
Automatic Encoding and Repair of Reactive High-Level Tasks with Learned Abstract Representations
We present a framework that, given a set of skills a robot can perform, ...
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04/14/2022
Procedural Content Generation using Neuroevolution and Novelty Search for Diverse Video Game Levels
Procedurally generated video game content has the potential to drastical...
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02/27/2022
Data Overlap: A Prerequisite For Disentanglement
Learning disentangled representations with variational autoencoders (VAE...
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02/01/2022
Investigating Transfer Learning in Graph Neural Networks
Graph neural networks (GNNs) build on the success of deep learning model...
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01/25/2022
Towards Objective Metrics for Procedurally Generated Video Game Levels
With increasing interest in procedural content generation by academia an...
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10/09/2021
Learning to Follow Language Instructions with Compositional Policies
We propose a framework that learns to execute natural language instructi...
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01/19/2020
Learning Options from Demonstration using Skill Segmentation
We present a method for learning options from segmented demonstration tr...
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01/14/2020
Quantisation and Pruning for Neural Network Compression and Regularisation
Deep neural networks are typically too computationally expensive to run ...
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01/06/2020
A Boolean Task Algebra for Reinforcement Learning
We propose a framework for defining a Boolean algebra over the space of ...
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01/02/2020
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 p...
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05/28/2019
Learning Portable Representations for High-Level Planning
We present a framework for autonomously learning a portable representati...
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07/12/2018
