Labs
Research groups working on symbol emergence and collective predictive coding.
Google DeepMind — Multi-Agent Research
PI: (Multiple PIs)
Multi-agent learning and emergent communication research at DeepMind, spanning cooperation, competition, language emergence, and societal-scale simulations of intelligent agents.
Theoretical Neurobiology Group (Friston Lab)
PI: Karl Friston
The Wellcome Trust Centre for Human Neuroimaging hosts the theoretical neurobiology group, which develops the free-energy principle and active inference as a unifying account of perception, action, and learning.
Human & Machine Learning Lab
PI: Brenden Lake
The lab develops computational models of how humans learn rich, structured concepts from limited experience, and how machines can do the same. Recent work has focused on systematic generalisation in neural networks.
Improbable AI Lab
PI: Pulkit Agrawal
Research at the intersection of robot learning, multi-agent systems, and emergent behaviour. The lab studies how communication, coordination, and generalisation arise in embodied agents trained at scale.
Taniguchi Lab — Symbol Emergence Systems
PI: Tadahiro Taniguchi
Research focused on symbol emergence, multimodal robotics, and the Collective Predictive Coding theory. The lab studies how concepts and language emerge from sensorimotor experience in artificial and biological agents.