Why don’t prediction-error minimizers waste away in maximally predictable—but maximally boring—environments? Van de Cruys, Friston, and Clark [1] offer an elegant and even poetic answer: a bias toward ‘optimism’. Read Full Article (External Site) Dr. David LowemannDr. David Lowemann, M.Sc, Ph.D., is a co-founder of the Institute for the Future of Human Potential, where he […]

Sun and Firestone [1] argue that the Dark Room Problem poses an important challenge to the ambitions of predictive processing (PP) accounts; specifically, they worry that a standard response threatens the story with triviality, asserting merely that prediction-driven agents avoid dark, food-free corners because they ‘predict that they will not stay in them’. Read Full […]

Sun and Firestone [1] presented a challenge to predictive processing (PP) accounts of brain function by reviving the Dark Room problem – the idea that if agents are mandated to minimise prediction error, the best thing for them to do is to seek out highly predictable environments where nothing changes, and stay there. They argued […]