AIhub monthly digest: October 2026 – neurosymbolic planning, time-series forecasting, and robots for the home

Welcome to our monthly digest, where you can catch up with any AIhub stories you may have missed, peruse the latest news, recap recent events, and more. This month, we chat to AI pioneer, Michael Littman, learn about time-series forecasting for clinical data, investigate evolutionary game theory for cybersecurity, and get the scoop on neuromorphic computing. In the latest interview in our series meeting AI pioneers, Michael Littman reflects on the evolution of reinforcement learning, the power of science communication, and how generative AI is changing the way we teach and learn. Mayra Elwes is a PhD student developing machine learning methods for clinical time-series data. She is working on practical strategies to evaluate methods in a more contextualised way and on improving existing domain adaptation methods specific to time-series forecasting.