A Common-Sense Planning Strategy for Ambient Intelligence

  • María J. Santofimia
  • Scott E. Fahlman
  • Francisco Moya
  • Juan C. López
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6277)


Systems for Ambient Intelligence contexts are expected to exhibit an autonomous and intelligent behavior, by understanding and reacting to the activities that take place in such contexts. These activities, specially those labeled as trivial or simple tasks, are carried out in an effortless manner by most people. In contrast to what it might be expected, computers have struggled to deal with these activities, while easily performing some others, such as high profile calculations, that are hard for humans. Imagine a situation where, while holding an object, the holder walks to a contiguous room. We effortlessly infer that the object is changing its location along with its holder. However, such inferences are not well addressed by computers due to their lack of common-sense knowledge and reasoning capability. Providing systems with these capabilities implies collecting a great deal of knowledge about everyday life and implementing inference mechanisms to derive new information from it. The work proposed here advocates a common-sense approach as a solution to the shortage of current systems for Ambient Intelligence.


Resource Description Framework Service Composition Semantic Model Ambient Intelligence Biometric Feature 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • María J. Santofimia
    • 1
  • Scott E. Fahlman
    • 2
  • Francisco Moya
    • 1
  • Juan C. López
    • 1
  1. 1.Computer Architecture and Networks Group, School of Computer ScienceUniversity of Castilla-La Mancha 
  2. 2.Language Technologies InstituteCarnegie Mellon UniversityPittsburghUSA

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