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Surrogate Infeasible Fitness Acquirement FI-2Pop for Procedural Content Generation



Roberto Gallotta , Kai Arulkumaran , L. B. Soros


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On the link between conscious function and general intelligence in humans and machines



Arthur Juliani , Kai Arulkumaran , Shuntaro Sasai , Ryota Kanai


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All You Need Is Supervised Learning: From Imitation Learning to Meta-RL With Upside Down RL



Kai Arulkumaran , Dylan R. Ashley , Jürgen Schmidhuber , Rupesh K. Srivastava


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Learning Relative Return Policies With Upside-Down Reinforcement Learning



Dylan R. Ashley , Kai Arulkumaran , Jürgen Schmidhuber , Rupesh Kumar Srivastava

* 5 pages in main text, 2 figures in main text 

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Diversity-based Trajectory and Goal Selection with Hindsight Experience Replay



Tianhong Dai , Hengyan Liu , Kai Arulkumaran , Guangyu Ren , Anil Anthony Bharath


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A Pragmatic Look at Deep Imitation Learning



Kai Arulkumaran , Dan Ogawa Lillrank


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Privileged Information Dropout in Reinforcement Learning



Pierre-Alexandre Kamienny , Kai Arulkumaran , Feryal Behbahani , Wendelin Boehmer , Shimon Whiteson


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Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation



Tianhong Dai , Kai Arulkumaran , Samyakh Tukra , Feryal Behbahani , Anil Anthony Bharath


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Sample-Efficient Reinforcement Learning with Maximum Entropy Mellowmax Episodic Control



Marta Sarrico , Kai Arulkumaran , Andrea Agostinelli , Pierre Richemond , Anil Anthony Bharath

* Workshop on Biological and Artificial Reinforcement Learning, NeurIPS 2019 

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Memory-Efficient Episodic Control Reinforcement Learning with Dynamic Online k-means



Andrea Agostinelli , Kai Arulkumaran , Marta Sarrico , Pierre Richemond , Anil Anthony Bharath

* Workshop on Biological and Artificial Reinforcement Learning, NeurIPS 2019 

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