Search Results for author: Daniel Majoral

Found 2 papers, 2 papers with code

Emergence of Adaptive Circadian Rhythms in Deep Reinforcement Learning

1 code implementation22 Jul 2023 Aqeel Labash, Florian Fletzer, Daniel Majoral, Raul Vicente

From a dynamical systems view, we demonstrate that the adaptation proceeds by the emergence of a stable periodic orbit in the neuron dynamics with a phase response that allows an optimal phase synchronisation between the agent's dynamics and the environmental rhythm.


Do deep reinforcement learning agents model intentions?

1 code implementation15 May 2018 Tambet Matiisen, Aqeel Labash, Daniel Majoral, Jaan Aru, Raul Vicente

In this work we test whether deep reinforcement learning agents explicitly represent other agents' intentions (their specific aims or goals) during a task in which the agents had to coordinate the covering of different spots in a 2D environment.

reinforcement-learning Reinforcement Learning (RL)

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