As is well-known by now, the universal AI agent AIXI is made up of two key components: Solomonoff Induction for universal sequential prediction, and expectimax search for planning. There are several proposed and reasonably effective approximations of the Solomonoff Induction component using the factored, binarised Context Tree Weighting algorithm [WST95, VNHUS09] and its generalisation to … More Approximating Solomonoff Induction
My phd student just got a new paper accepted at the upcoming AAAI Conference on Artificial Intelligence. Here’s the abstract of the paper: Prior approximations of AIXI, a Bayesian optimality notion for general reinforcement learning, can only approximate AIXI’s Bayesian environment model using an a-priori defined set of models. This is a fundamental source of … More Dynamic Knowledge Injection for AIXI Agents
There are many different definitions of Artificial Intelligence in the literature, all are suggestive and insightful. However, at the end of the day, I think there is really one simple enough to be understood and formalised rigorously. This is John McCarthy’s original definition of AI from 1955: “the science and engineering of making intelligent machines”. … More A Simple Definition of Artificial Intelligence
Mental Models 4 Life 