Weshowthat by inferring parametexdomainsof planningoperators,given the definitions of the operators and the initial and goal conditions, we can often speed up the planning process...
Learning from experimentation allows a system to acquire planning domain knowledge by correcting its knowledge when an action execution fails. Experiments are designed and planned...
A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintaining the planning knowledge base (KB). Pla...
The principle of least commitment was embraced early in planning research. Hierarchical task networks (HTNs)reason about high-level tasks without committing to specific low-level ...
We have been examining mixed-initiative planning systems in the context of command and control or logistical overview situations. In such environments, the human and the computer ...
George Ferguson, James F. Allen, Bradford W. Mille...
An increasing number of planners can handle uncertainty in the domain or in action outcomes. However, less work has addressed building plans when the planner's world can chan...
Mostexisting decision-theoretic planners represent uncertainty about the state of the world with a precisely specified probability distribution over world states. This representat...
Statistical exploratory data analysis (EDA) poses a di cult search problem. However, the EDA process lends itself to a planning formulation. We have built a system, called Aide, t...