Leap Before You Look: Information Gathering in the PUCCINI Planner

Keith Golden

Most of the work in planning with incomplete information takes a "look before you leap" perspective: Actions must be guaranteed to have their intended effects before they can be executed. We argue that this approach is impossible to follow in many real-world domains. The agent may not have enough information to ensure that an action will have a given effect in advance of executing it. This paper describes PUCCINI, a partial-order planner used to control the Internet Softbot. PUCCINI takes a different approach to coping with incomplete information: "Leap before you look!" PUCCINI doesn’t require actions to be known to have the desired effects before execution. However, it still maintains soundness, by requiring the effects to be verified eventually. We discuss how this is achieved using a simple generalization of causal links.


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