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Fast and slow curiosity for high-level exploration in reinforcement learning

Applied intelligence (Dordrecht, Netherlands), 2021-02, Vol.51 (2), p.1086-1107

2021

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Towards Interpretable Reinforcement Learning with State Abstraction Driven by External Knowledge

IEICE Transactions on Information and Systems, 2020/10/01, Vol.E103.D(10), pp.2143-2153

2020

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Shared communication for coordinated large-scale reinforcement learning control

SICE Journal of Control, Measurement, and System Integration, 2023-12, Vol.ahead-of-print (ahead-of-print), p.1-11

2023

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Skill-based curiosity for intrinsically motivated reinforcement learning

Machine learning, 2020-03, Vol.109 (3), p.493-512

2020

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Interpretable Imitation Learning with Symbolic Rewards

ACM transactions on intelligent systems and technology, 2023-12, Vol.15 (1), p.1-34, Article 4

2023

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Hierarchical learning from human preferences and curiosity

Applied intelligence (Dordrecht, Netherlands), 2022-05, Vol.52 (7), p.7459-7479

2022

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Goal-driven active learning

Autonomous agents and multi-agent systems, 2021-10, Vol.35 (2), Article 44

2021

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Exploration via Progress-Driven Intrinsic Rewards

Artificial Neural Networks and Machine Learning – ICANN 2020, p.269-281

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Intrinsically Motivated Lifelong Exploration in Reinforcement Learning

Advances in Artificial Intelligence, 2021, Vol.1357, p.109-120

2021

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Combining deep reinforcement learning with prior knowledge and reasoning

Applied computing review : a publication of the Special Interest Group on Applied Computing, 2018-07, Vol.18 (2), p.33-45

2018

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Abstracting Reinforcement Learning Agents with Prior Knowledge

PRIMA 2018: Principles and Practice of Multi-Agent Systems, p.431-439

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Data-Efficient Reinforcement Learning from Controller Guidance with Integrated Self-Supervision for Process Control

IFAC-PapersOnLine, 2022, Vol.55 (7), p.863-868

2022

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Deep reinforcement learning boosted by external knowledge

Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 2018, p.331-338

2018

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Local Control is All You Need: Decentralizing and Coordinating Reinforcement Learning for Large-Scale Process Control

2022 61st Annual Conference of the Society of Instrument and Control Engineers (SICE), 2022, p.468-474

2022

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Publication outcome of abstracts presented at an Anesthesiology and Critical Care Medicine meeting: Does being a junior presenter matter?

Journal of clinical anesthesia, 2020-03, Vol.60, p.49-50

2020

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Fast and slow curiosity for high-level exploration in reinforcement learning

Towards Interpretable Reinforcement Learning with State Abstraction Driven by External Knowledge

Shared communication for coordinated large-scale reinforcement learning control

Skill-based curiosity for intrinsically motivated reinforcement learning

Interpretable Imitation Learning with Symbolic Rewards

Hierarchical learning from human preferences and curiosity

Goal-driven active learning

Exploration via Progress-Driven Intrinsic Rewards

Intrinsically Motivated Lifelong Exploration in Reinforcement Learning

Combining deep reinforcement learning with prior knowledge and reasoning

Abstracting Reinforcement Learning Agents with Prior Knowledge

Data-Efficient Reinforcement Learning from Controller Guidance with Integrated Self-Supervision for Process Control

Deep reinforcement learning boosted by external knowledge

Local Control is All You Need: Decentralizing and Coordinating Reinforcement Learning for Large-Scale Process Control

Publication outcome of abstracts presented at an Anesthesiology and Critical Care Medicine meeting: Does being a junior presenter matter?

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