The U.S. Military is investigating ways to take advantage of modern information systems, simulation techniques, and artificial intelligence methodologies to gain information dominance over potential adversaries. One of the research areas being explored is the implementation of a new approach to planning called “anticipatory planning and adaptive execution” that merges planning, execution, and m...

We discuss the problem of inspecting an underwater structure, such as a submerged ship hull, with an autonomous underwater vehicle (AUV). Unlike a large body of prior work, we focus on planning the views of the AUV to improve the quality of the inspection, rather than maximizing the accuracy of a given data stream. We formulate the inspection planning problem as an extension to Bayesian active ...

This paper presents an adaptive planning system, called HAPRC, which automatically fine-tunes its planning parameters according to the morphology of the problem in hand, through a combination of Planning, Machine Learning and Knowledge-Based techniques. The adaptation is guided by a rule-based system that sets planner configuration parameters based on measurable characteristics of the problem i...

We describe an interaction console for interactive proof exercises using proof planning as back-engine. Based on the proof planning situation, the console offers suggestions for proof steps. These suggestions can dynamically be adapted, e.g. to the user and to pedagogical criteria. This adaptive configuration is possible because the suggestion mechanism and proof planning are clearly separated....

Adaptive automata have been developed as a formal device intended to handle complex input languages, featuring context dependencies. As other adaptive formalisms, adaptive automata collect information from its inputs and may change its own behavior in response to that information. Therefore, such formalisms are able to dynamically acquire and represent knowledge. Independent navigation require ...

A wide variety of operational issues were encountered with the planning and implementation of an adaptive, dose-finding, seamless phase 2/3 trial for a diabetes therapeutic. Compared with a conventional design, significant upfront planning was required, as well as earlier, more integrated cross-functional coordination. The existing infrastructure necessitated greater flexibility to meet the nee...

In domain independent heuristic planning there is a number of planning systems with very good performance on some problems and very poor on others. Few attempts have been made in the past to explain this phenomenon. In this paper we use machine learning techniques to discover knowledge hidden in the dynamics of the planning process that would relate specific characteristics of a planning proble...

Realistic environments for motion planning problems typically consist of multiple areas, e.g., in a house there are rooms, hallways, and doorways. Decomposition of the environment into smaller areas, or regions, has been shown to impact the quality of planning for adaptive methods. Also other complex problems, such as planning for groups of agents with environmental preferences, can be aided wi...