There has been much recent work on the use of abstraction to improve planning behavior and cost. Another technique for dealing with the inherently explosive cost of planning is localization. This paper compares the relative strengths of localization and abstraction in reducing planning search cost. In particular, localization is shown to subsume abstraction. Localization techniques can model th...

There has been much recent work on the use of abstraction to improve planning behavior and cost. Another technique for dealing with the inherently explosive cost of planning is localization. This paper compares the relative strengths of localization and abstraction in reducing planning search cost. In particular, localization is shown to subsume abstraction. Localization techniques can model th...

Planning is an artificial intelligence problem with a wide range of real-world applications. Genetic algorithms, neural networks, and simulated annealing are heuristic search methods often used to solve complex optimization problems. In this paper, we propose a genetic approach to planning in the context of workflow management and process coordination on a heterogenous grid. We report results f...

This was the eighth in a regular series that started in 1997. T he Workshop on Planning and Scheduling for Space (IWPSS) fo-cuses on the technical challenges and opportunities facing the AI planning and scheduling community when addressing the needs of a wide range of space-based applications, from mission operations to autonomy in space exploration vehicles. There have been eight workshops in ...

Recent developments in decision-making research are bringing the topic of planning back to center stage in cognitive science. This renewed interest reopens an old, but still unanswered question: how exactly does planning happen? What are the underlying information processing operations and how are they implemented in the brain? Although a range of interesting possibilities exists, recent work h...