Computer Science and Evolutionary Biology Lead
Dr. Richard Watson studies evolution, learning, cognition and society and their unifying algorithmic principles. He studied Artificial Intelligence and Adaptive Systems at Sussex University, then PhD Computer Science at Brandeis in Boston. His current work deepens the unification of evolution and learning – specifically, with connectionist models of learning and cognition, familiar in neural network research – to address topics such as evolvability, ecological memory, evolutionary transitions in individuality (ETIs), phenotypic plasticity, the extended evolutionary synthesis, collective intelligence and ‘design’. He has also developed new computational methods for combinatorial optimisation (deep optimisation), exploiting a unification of deep learning and ‘deep evolution’ (i.e. ETIs). He is author of “Compositional evolution” (MIT Press), was featured as “one to watch in AI” in Intelligent Systems magazine, and his paper “How Can Evolution Learn” in TREE, attracted the ISAL award 2016. He is now a professor at the University of Southampton, where he is a member of the Agents, Interaction and Complexity group and the Institute for Life Sciences.