Hi colleagues,
We are offering a new track as part of the ICAPS (International Conference on Automated Planning and Scheduling) conference this year on planning and learning. (See blurb below.) Given the centrality of planning and learning to UAI, I wanted to alert the community and encourage you to submit. The abstract deadline is November 18th. Thanks! -Alan Fern and Michael Littman http://icaps17.icaps-conference.org/learning-track In 2017, ICAPS will run a Planning and Learning track as part of the main conference. Machine learning has impacted all aspects of Artificial Intelligence and Computer Science, and planning is no exception. Indeed, the planning and scheduling community have a long history of incorporating learning machinery into planning systems as well as deploying planning systems for learning. This new track provides an opportunity for the AI planning and scheduling community to engage directly with developments in the learning community for the benefits of both. The Planning and Learning track aims to present research at the intersection of the fields of machine learning and planning & scheduling. In particular, we are interested in work that draws substantially from the objectives, techniques, or methodologies of both fields. Topics include, but are not limited to: * Reinforcement learning; * Learning to improve the effectiveness of planning systems; * Learning domain models; * Planning in learned domain models; * Learning effective heuristics and other forms of control knowledge; * Planning applied to automating machine learning systems; * Applications that involve a combination of learning and planning
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