Encyclopedia of Complexity and Systems Science

Living Edition
| Editors: Robert A. Meyers

Learning and Planning (Intelligent Systems)

Living reference work entry
DOI: https://doi.org/10.1007/978-3-642-27737-5_308-2

Introduction

The ability to produce knowledge about past experiences and exploit that knowledge in an operational context in later problem-solving and planning sessions is an important attribute of any intelligent system, human- or AI-based alike. Automated planning and learning is a research paradigm that focuses on the development of intelligent systems and technologies that combine the ability to make decisions and generate courses of actions (i.e., plans) with the capability to reason and produce knowledge about past experiences, future problems that the system needs to tackle, and strategies about how to tackle them.

Probably the first work that laid a formal treatment for this combination is the early planning system STRIPS (Fikes and Nilsson 1971), developed in the early 1970s. The STRIPS planning system was an evidence that planning and learning are usually two pieces of an intelligent system, where the knowledge acquired via learning is used to enhance the problem-solving and...

Keywords

Planning Problem Planning Domain Control Rule Target Concept Domain Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgments

This work was partly supported by DARPA’s “Mission-oriented Resilient Cloud (MRC)” (Contract #: FA865011C7191) and Office of Naval Research (ONR)’s “Computational Methods for Decision Making” program (Contract #: N0001412C0239). An earlier version of this work was partly supported by DARPA’s Transfer Learning and Integrated Learning programs. The opinions in this entry are those of the author and do not necessarily reflect the opinions of the funders.

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© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Smart Information Flow Technologies (SIFT)MinneapolisUSA