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A Concise Introduction to Models and Methods for Automated PlanningPlanning and Autonomous Behavior

A Concise Introduction to Models and Methods for Automated Planning: Planning and Autonomous... [Planning is the model-based approach to autonomous behavior where the agent selects the action to do next using a model of how actions and sensors work, what is the current situation, and what is the goal to be achieved. In this chapter, we contrast programming, learning, and model-based approaches to autonomous behavior, and present some of the models in planning that will be considered in more detail in the following chapters. These models are all general in the sense that they are not bound to specific problems or domains. This generality is intimately tied to the notion of intelligence which requires the ability to deal with new problems. The price for generality is computational: planning over these models when represented in compact form is intractable in the worst case. A main challenge in planning is thus the automated exploitation of problem structure for scaling up to large and meaningful instances that cannot be handled by brute force methods.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Concise Introduction to Models and Methods for Automated PlanningPlanning and Autonomous Behavior

Part of the Synthesis Lectures on Artificial Intelligence and Machine Learning Book Series
Geffner, Hector; Bonet, Blai
Springer Journals — Jan 1, 2013
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12 pages

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Publisher
Springer International Publishing
Copyright
© Springer Nature Switzerland AG 2013
ISBN
978-3-031-00436-0
Pages
1 –13
DOI
10.1007/978-3-031-01564-9_1
Publisher site
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Abstract

[Planning is the model-based approach to autonomous behavior where the agent selects the action to do next using a model of how actions and sensors work, what is the current situation, and what is the goal to be achieved. In this chapter, we contrast programming, learning, and model-based approaches to autonomous behavior, and present some of the models in planning that will be considered in more detail in the following chapters. These models are all general in the sense that they are not bound to specific problems or domains. This generality is intimately tied to the notion of intelligence which requires the ability to deal with new problems. The price for generality is computational: planning over these models when represented in compact form is intractable in the worst case. A main challenge in planning is thus the automated exploitation of problem structure for scaling up to large and meaningful instances that cannot be handled by brute force methods.]

Published: Jan 1, 2013

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