F. Pigozzi

The Informationally Integrated Alignment Hypothesis: Integrated Information Aligns with and Predicts Final Reward in Reinforcement Learning Agents

This work focused on Reinforcement Learning of neural-network agents across a range of environmental conditions, encompassing different algorithms, agent architectures, and six environments arranged along a complexity spectrum and suggested a Causally Emergent Alignment Hypothesis: successful agents exhibited integrate...