Refinement Planning: Status and Prospectus

Refinement lanning: Status an

Most current-day AI planning systems operate by iteratively refining a partial plan until it meets the goal requirements. In the past five years, significant progress has been made in our understanding of the spectrum and capabilities of such refinement planners. In this talk, I will summarize this understanding in terms of a unified framework for refinement planning and discuss several current...

Prospectus for Recording EEG and ERP in Infants

Area-based refinement for selection of reserve sites with the benefit-function approach.

Optimization of resource use is necessary for efficient conservation planning. Many reserve-selection algorithms aim to identify representative but inexpensive networks, which may lead to selecting small sites due to their lower costs and collectively higher species richness. Nevertheless, larger sites would be preferable regarding species' long-term persistence. An area-based refinement can be...

Planning as Refinement Search: A unified framework for comparative analysis of Search Space Size and Performance

In spite of the long history of classical planning, there has been very little comparative analysis of the search space characteristics of the multitude of existing planning algorithms. This has seriously inhibited efforts to fruitfully intergrate various approaches. In this paper we show that viewing planning as a general refinement search provides a unified framework for comparing the search ...

Focusing Agricultural Education Research: Strategies for the Professor

Universities are in a period of transition driven by profound changes in society. “Strategic planning” is a common term used on many campuses to describe an ongoing process of program evaluation and refinement. Colleges of agriculture and education, the home of most agricultural education programs, are identifying priorities and clarifying missions. To provide a basis for decision-making and re...