Policy conflict resolution in IoT via planning

Title Policy conflict resolution in IoT via planning
Author Göynügür, Emre, Bernardini, S., Mel, G. de, Talamadupula, K., Şensoy, Murat
Publication Date: 2017
Publication Place - Advances in Artificial Intelligence
Subject IoT, Semantic web, Policy, Conflict resolution, Planning
Type Document
Language English
Digital Yes
Manuscript No
Library: Özyeğin University
Library Asset ID 0302-9743
Record ID 7afa5bb5-85e3-4acd-b043-dae41b779dad
Library Location Computer Science
Date 2017
Sample Text With the explosion of connected devices to automate tasks, manually governing interactions among such devices—and associated services—has become an impossible task. This is because devices have their own obligations and prohibitions in context, and humans are not equipped to maintain a bird’s-eye-view of the environment. Motivated by this observation, in this paper, we present an ontology-based policy framework which can efficiently detect policy conflicts and automatically resolve such using an AI planner.
DOI 10.1007/978-3-319-57351-9_22
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Policy conflict resolution in IoT via planning

Author Göynügür, Emre, Bernardini, S., Mel, G. de, Talamadupula, K., Şensoy, Murat
Publication Date 2017
Publication Place - Advances in Artificial Intelligence
Subject IoT, Semantic web, Policy, Conflict resolution, Planning
Type Document
Language English
Digital Yes
Manuscript No
Library Özyeğin University
Library Asset ID 0302-9743
Record ID 7afa5bb5-85e3-4acd-b043-dae41b779dad
Library Location Computer Science
Date 2017
Sample Text With the explosion of connected devices to automate tasks, manually governing interactions among such devices—and associated services—has become an impossible task. This is because devices have their own obligations and prohibitions in context, and humans are not equipped to maintain a bird’s-eye-view of the environment. Motivated by this observation, in this paper, we present an ontology-based policy framework which can efficiently detect policy conflicts and automatically resolve such using an AI planner.
DOI 10.1007/978-3-319-57351-9_22
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