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Learning and Planning (Intelligent Systems)

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Encyclopedia of Complexity and Systems Science

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Definition of the Subject

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 the 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  [17], developed in 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...

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Notes

  1. 1.

    HTN planners may have other kinds of knowledge artifacts as well. For example, the \( { \textsf{SHOP2} } \) planner [39] has axioms that can be used to infer conditions about the current state.

Abbreviations

Automated planning:

Automated Planning is the problem of generating a sequence of actions for an initial configuration of the world that, when executed, produces a final configuration that satisfies a specified set of goal conditions.

Planning knowledge:

Almost all of successful AI planning systems developed in recent years use some sort of search-control knowledge for effective planning. Sometimes the planning knowledge is specified in terms of domain-independent heuristics, i.?e., heuristics intended for use in many different planning domains, and sometimes they are specified in terms of domain-specific control knowledge (i.?e., tailored to a specific problem domain).

Learning for problem-solving and planning:

Learning for planning is the process of acquiring auxiliary knowledge related to a planning problem, which can be used by a planning system to understand better the underlying planning domain and to control its search for generating plans in that domain.

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Acknowledgments

This work was supported by DARPA's Transfer Learning and Integrated Learning programs. The opinions in this paper are those of the author and do not necessarily reflect the opinions of the funders.

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Authors and Affiliations

  1. Institute of Advanced Computer Studies and Department of Computer Science, University of Maryland, College Park, USA

    Ugur Kuter

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  1. Ugur Kuter
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  1. RAMTECH LIMITED, 122 Escalle Lane, Larkspur, CA, 94939, USA

    Robert A. Meyers Ph. D. (Editor-in-Chief) (Editor-in-Chief)

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Kuter, U. (2009). Learning and Planning (Intelligent Systems). In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30440-3_308

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