Search Results for author: Zafeirios Fountas

Found 7 papers, 1 papers with code

Bayesian sense of time in biological and artificial brains

no code implementations14 Jan 2022 Zafeirios Fountas, Alexey Zakharov

Enquiries concerning the underlying mechanisms and the emergent properties of a biological brain have a long history of theoretical postulates and experimental findings.

Bayesian Inference

Exploration and preference satisfaction trade-off in reward-free learning

no code implementations ICML Workshop URL 2021 Noor Sajid, Panagiotis Tigas, Alexey Zakharov, Zafeirios Fountas, Karl Friston

In this paper, we pursue the notion that this learnt behaviour can be a consequence of reward-free preference learning that ensures an appropriate trade-off between exploration and preference satisfaction.

OpenAI Gym

Episodic Memory for Learning Subjective-Timescale Models

no code implementations3 Oct 2020 Alexey Zakharov, Matthew Crosby, Zafeirios Fountas

In model-based learning, an agent's model is commonly defined over transitions between consecutive states of an environment even though planning often requires reasoning over multi-step timescales, with intermediate states either unnecessary, or worse, accumulating prediction error.

Deep active inference agents using Monte-Carlo methods

1 code implementation NeurIPS 2020 Zafeirios Fountas, Noor Sajid, Pedro A. M. Mediano, Karl Friston

In a more complex Animal-AI environment, our agents (using the same neural architecture) are able to simulate future state transitions and actions (i. e., plan), to evince reward-directed navigation - despite temporary suspension of visual input.

Multimodal Data Fusion based on the Global Workspace Theory

no code implementations26 Jan 2020 Cong Bao, Zafeirios Fountas, Temitayo Olugbade, Nadia Bianchi-Berthouze

We propose a novel neural network architecture, named the Global Workspace Network (GWN), which addresses the challenge of dynamic and unspecified uncertainties in multimodal data fusion.

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