Search Results for author: Kyriacos Nikiforou

Found 8 papers, 3 papers with code

Hierarchical Reinforcement Learning in Complex 3D Environments

no code implementations28 Feb 2023 Bernardo Avila Pires, Feryal Behbahani, Hubert Soyer, Kyriacos Nikiforou, Thomas Keck, Satinder Singh

Hierarchical Reinforcement Learning (HRL) agents have the potential to demonstrate appealing capabilities such as planning and exploration with abstraction, transfer, and skill reuse.

Hierarchical Reinforcement Learning reinforcement-learning +1

Neural Algorithmic Reasoning with Causal Regularisation

no code implementations20 Feb 2023 Beatrice Bevilacqua, Kyriacos Nikiforou, Borja Ibarz, Ioana Bica, Michela Paganini, Charles Blundell, Jovana Mitrovic, Petar Veličković

We evaluate our method on the CLRS algorithmic reasoning benchmark, where we show up to 3$\times$ improvements on the OOD test data.

Data Augmentation

Task-driven Discovery of Perceptual Schemas for Generalization in Reinforcement Learning

no code implementations29 Sep 2021 Wilka Torrico Carvalho, Andrew Kyle Lampinen, Kyriacos Nikiforou, Felix Hill, Murray Shanahan

Taking inspiration from cognitive science, we term representations for reoccurring segments of an agent's experience, "perceptual schemas".

Object reinforcement-learning +1

AlignNet: Self-supervised Alignment Module

no code implementations25 Sep 2019 Antonia Creswell, Luis Piloto, David Barrett, Kyriacos Nikiforou, David Raposo, Marta Garnelo, Peter Battaglia, Murray Shanahan

The natural world consists of objects that we perceive as persistent in space and time, even though these objects appear, disappear and reappear in our field of view as we move.

Object Question Answering

An Explicitly Relational Neural Network Architecture

2 code implementations ICML 2020 Murray Shanahan, Kyriacos Nikiforou, Antonia Creswell, Christos Kaplanis, David Barrett, Marta Garnelo

With a view to bridging the gap between deep learning and symbolic AI, we present a novel end-to-end neural network architecture that learns to form propositional representations with an explicitly relational structure from raw pixel data.

Relational Reasoning

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