scholarly journals Towards a Fuzzy Context Logic

2021 ◽  
Author(s):  
Hedda Schmidtke
Keyword(s):  
Fuzzy Logic ◽  
Pervasive Computing ◽  
Intelligent Systems ◽  
Close Connection ◽  
Computing Systems ◽  
Sensor Actuator ◽  
Logical Language ◽  
Explainable Ai

A key step towards trustworthy, reliable and explainable, AI is bridging the gap between the quantitative domain of sensor-actuator systems and the qualitative domain of intelligent systems reasoning. Fuzzy logic is a well-known formalism suitable for aiming at this gap, featuring a quantitative mechanism that at the same time adheres to logical principles. Context logic is a two-layered logical language originally aimed at pervasive computing systems for reasoning about and within context, i.e., changing logical environments. Both logical languages are linguistically motivated. This chapter uncovers the close connection between the two logical languages presenting two new results. First, a proof is presented that context logic with a lattice semantics can be understood as an extension of fuzzy logic. Second, a fuzzification for context logic is proposed. The resulting language, which can be understood as a two-layered fuzzy logic or as a fuzzified context logic, expands both fields in a novel manner.

A Security Architecture Based on Trust Management for Pervasive Computing Systems

2005 ◽  
Author(s):  
Lalana Kagal ◽  
Jeffrey Undercoffer ◽  
Filip Perich ◽  
Anupam Joshi ◽  
Tim Finin
Keyword(s):  
Pervasive Computing ◽  
Trust Management ◽  
Security Architecture ◽  
Computing Systems

Ontology-based models in pervasive computing systems

2007 ◽  
Vol 22 (4) ◽  
pp. 315-347 ◽  
Author(s):  
JUAN YE ◽  
LORCAN COYLE ◽  
SIMON DOBSON ◽  
PADDY NIXON
Keyword(s):  
Pervasive Computing ◽  
Information Exchange ◽  
Next Generation ◽  
Computing Systems ◽  
Diverse Range ◽  
Shared Representations ◽  
Pervasive Systems ◽  
Structured Information ◽  
Compare And Contrast

AbstractPervasive computing is by its nature open and extensible, and must integrate the information from a diverse range of sources. This leads to a problem of information exchange, so sub-systems must agree on shared representations. Ontologies potentially provide a well-founded mechanism for the representation and exchange of such structured information. A number of ontologies have been developed specifically for use in pervasive computing, none of which appears to cover adequately the space of concerns applicable to application designers. We compare and contrast the most popular ontologies, evaluating them against the system challenges generally recognized within the pervasive computing community. We identify a number of deficiencies that must be addressed in order to apply the ontological techniques successfully to next-generation pervasive systems.

scholarly journals Context-Aware User Modeling and Semantic Interoperability in Smart Home Environments

2015 ◽  
Vol 7 (3) ◽  
pp. 17-50
Author(s):  
Giorgos Siolas ◽  
George Caridakis ◽  
Phivos Mylonas ◽  
Giorgos Stratogiannis ◽  
Stefanos Kollias ◽  
...  
Keyword(s):  
Pervasive Computing ◽  
Smart Home ◽  
User Modeling ◽  
Collective Intelligence ◽  
Context Modeling ◽  
Home Environments ◽  
Computing Systems ◽  
Knowledge Based ◽  
Context Cues ◽  
Smart Home Environments

The current paper provides an overview on how user modeling, context awareness and content adaptation in Smart Home environments may be handled formally in order to capture the semantics that emerge from a newly introduced user experience: SandS is in fact a complete ecosystem of users within a social network, creating and exchanging content in the form of so-called recipes and developing a collective intelligence which adapts its operation through appropriate feedback provided by the user. The authors will approach SandS from the user's perspective and illustrate how users and their relationships can be modeled through a number of fuzzy stereotypical profiles. Additionally, context modeling in pervasive computing systems and especially in the Smart Home paradigm will be examined through appropriate representation of context cues in the overall interaction. Finally, the authors will investigate how users and system services although using languages of different semantic expressiveness can inter-operate successfully thanks to appropriate knowledge-based expert mappings.

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