Session Overview Planning

Abstract

When we discuss autonomous robots, we think of robots that move around, interacting with people and making changes in the world. The problem of actually choosing motor commands to achieve high level goals — such as moving to a desired destination or answering a query from a human — typically involves planning. Planning is of course one of the central questions of artificial intelligence, and the planning field has moved a long way from the early days when planning meant searching for a sequence of abstract actions that satisfied some symbolic predicate. Robots can now learn their own representations through statistical inference procedures, they can now reason using different representations and they can reason in worlds where action can have stochastic outcomes.