Artificial Intelligence Planning for Ambient Environments

  • J. BidotEmail author
  • S. Biundo


In this chapter, we describe how Artificial Intelligence planning techniques are used in The Adapted and TRusted Ambient eCOlogies (ATRACO) in order to provide Sphere Adaptation. We introduce the Planning Agent (PA) which plays a central role in the realization and the structural adaptation of activity spheres. Based on particular information included in the ontology of the execution environment, the PA delivers workflows that consist of the basic activities to be executed in order to achieve a user’s goals. The PA encapsulates a search engine for hybrid planning–the combination of hierarchical task network planning and partial-order causal-link planning. In this chapter, we describe a formal framework and a development platform for hybrid planning, PANDA. This platform allows for the implementation of many search strategies, and we explain how we realize the search engine of the PA by adapting and configuring PANDA specifically for addressing planning problems that are part of the ATRACO service composition. We describe how the PA interacts with the Sphere Manager and the Ontology Manager in order to create planning problems dynamically and generate workflows in the ATRACO-BPEL language. In addition, an excerpt of a planning domain for ATRACO is provided.


Service Composition Planning Agent Partial Plan Abstract Service Abstract Task 
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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© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Institute of Artificial IntelligenceUlm UniversityUlmGermany

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