A theory of action for multi-agent planning
Distributed Artificial Intelligence
HTN planning: complexity and expressivity
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Commonsense Reasoning
Journal of Biomedical Informatics
Marker-Passing inference in the scone knowledge-base system
KSEM'06 Proceedings of the First international conference on Knowledge Science, Engineering and Management
What planner for ambient intelligence applications?
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A framework for advanced home service design and management
IEEE Transactions on Consumer Electronics
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part I
A Rule-Based Approach to Automatic Service Composition
International Journal of Ambient Computing and Intelligence
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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.