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08/14/2023
Current Status and Trends of Engineering Entrepreneurship Education in Australian Universities
This research sheds light on the present and future landscape of Enginee...
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05/06/2023
Weighted Point Cloud Normal Estimation
Existing normal estimation methods for point clouds are often less robus...
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10/11/2022
Broad-persistent Advice for Interactive Reinforcement Learning Scenarios
The use of interactive advice in reinforcement learning scenarios allows...
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10/07/2022
Elastic Step DQN: A novel multi-step algorithm to alleviate overestimation in Deep QNetworks
Deep Q-Networks algorithm (DQN) was the first reinforcement learning alg...
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07/07/2022
Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios
Explainable artificial intelligence is a research field that tries to pr...
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07/04/2022
Masked Autoencoders in 3D Point Cloud Representation Learning
Transformer-based Self-supervised Representation Learning methods learn ...
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10/15/2021
A Broad-persistent Advising Approach for Deep Interactive Reinforcement Learning in Robotic Environments
Deep Reinforcement Learning (DeepRL) methods have been widely used in ro...
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08/20/2021
Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey
Broad Explainable Artificial Intelligence moves away from interpreting i...
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08/18/2021
Explainable Deep Reinforcement Learning Using Introspection in a Non-episodic Task
Explainable reinforcement learning allows artificial agents to explain t...
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07/07/2021
Levels of explainable artificial intelligence for human-aligned conversational explanations
Over the last few years there has been rapid research growth into eXplai...
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03/17/2021
A Practical Guide to Multi-Objective Reinforcement Learning and Planning
Real-world decision-making tasks are generally complex, requiring trade-...
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02/04/2021
Persistent Rule-based Interactive Reinforcement Learning
Interactive reinforcement learning has allowed speeding up the learning ...
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09/21/2020
Human Engagement Providing Evaluative and Informative Advice for Interactive Reinforcement Learning
Reinforcement learning is an approach used by intelligent agents to auto...
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08/11/2020
A Comparison of Humanoid Robot Simulators: A Quantitative Approach
Research on humanoid robotic systems involves a considerable amount of c...
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07/07/2020
Deep Reinforcement Learning with Interactive Feedback in a Human-Robot Environment
Robots are extending their presence in domestic environments every day, ...
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07/03/2020
A Conceptual Framework for Externally-influenced Agents: An Assisted Reinforcement Learning Review
A long-term goal of reinforcement learning agents is to be able to perfo...
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06/24/2020
Explainable robotic systems: Interpreting outcome-focused actions in a reinforcement learning scenario
Robotic systems are more present in our society every day. In human-robo...
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05/05/2020
Discrete-to-Deep Supervised Policy Learning
Neural networks are effective function approximators, but hard to train ...
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04/14/2020
A Demonstration of Issues with Value-Based Multiobjective Reinforcement Learning Under Stochastic State Transitions
We report a previously unidentified issue with model-free, value-based a...
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02/04/2014