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Alvaro is interested in the teleonomic and teleological principles of living beings and the prospect of babysitting artificial agents that can develop their own values, drives, goals and purpose in life just like those in nature. Before coming to Queen Mary, Alvaro spent some time in Sussex learning about evolutionary systems and in the University of Edinburgh studying neuroscience and machine learning.

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GAIG Publications

2023

2022

2021

• 2021 Generalising Discrete Action Spaces with Conditional Action Trees
  Bamford, Christopher and Ovalle, Alvaro, in arXiv:2104.07294, 2021.
  pubs-2021  arxiv  strategy-games  reinforement-learning  action-spaces
  
  

2020

• IWAI 2020 Modulation of viability signals for self-regulatory control
  Ovalle, Alvaro and Lucas, Simon M, in International Workshop on Active Inference, pp. 101-113, 2020.
  pubs-2020  ieee-cog  reinforcement-learning
  
  
• IEEE COG 2020 Bootstrapped model learning and error correction for planning with uncertainty in model-based RL
  Ovalle, Alvaro and Lucas, Simon M, in IEEE Conference on Games (CoG), pp. 495-502, 2020.
  pubs-2020  ieee-cog  reinforcement-learning  rhea