Continuing Plan Quality Optimisation
Finding high quality plans for large planning problems is hard. Although some current anytime planners are often able to improve plans quickly, they tend to reach a limit at which the plans produced are still very far from the best possible, but these planners fail to find any further improvement, even when given several hours of runtime. We present an approach to continuing plan quality optimisation at larger time scales, and its implementation in a system called BDPO2. Key to this approach...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of Artificial Intelligence Research|
|Access Rights:||Open Access|
|01_Siddiqui_Continuing_Plan_Quality_2015.pdf||1.13 MB||Adobe PDF|
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