An Artificial Intelligence-Driven Smart Home Towards Energy Efficiency: An Overview and Conceptual Model

AbstractArtificial Intelligence applications often require to maintain a knowledge base about the observed environment. In particular, when the current knowledge is inconsistent with new information, it has to be updated. Such inconsistency can be due to erroneous assumptions or to changes in the environment. Here we considered the second case, and develop a knowledge update algorithm based on event logic that takes into account constraints according to which the environment can evolve. These constraints take the form of events that modify the environment in a well-defined manner. The belief update triggered by a new observation is thus explained by a sequence of events. We then apply this algorithm to the problem of locating people in a smart home and show that taking into account past information and move’s constraints improves location inference.

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Energy Efficiency of Photonic Convolution for Artificial Intelligence Workloads

10.1109/sips52927.2021.00052 ◽

2021 ◽

Author(s):

Jonas Weiss ◽

Pascal Stark ◽

Lorenz K. Muller ◽

Folkert Horst ◽

Roger Dangel ◽

...

Keyword(s):

Artificial Intelligence ◽

Energy Efficiency

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Artificial Intelligence, Big Data, and Value Co-creation: A Conceptual Model

The Fourth Industrial Revolution: Implementation of Artificial Intelligence for Growing Business Success - Studies in Computational Intelligence ◽

10.1007/978-3-030-62796-6_28 ◽

2021 ◽

pp. 475-483

Author(s):

Muneer Abbad ◽

Faten Jaber ◽

Kholoud AlQeisi ◽

Shorouq Eletter

Keyword(s):

Artificial Intelligence ◽

Big Data ◽

Conceptual Model

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On distributed artificial intelligence

The Knowledge Engineering Review ◽

10.1017/s0269888900004367 ◽

1988 ◽

Vol 3 (1) ◽

pp. 21-57 ◽

Cited By ~ 17

Author(s):

Luis Eduardo ◽

Castillo Hern

Keyword(s):

Artificial Intelligence ◽

Conceptual Model ◽

Intelligent Agents ◽

Distributed Artificial Intelligence ◽

Agent Interaction ◽

Multi Agent

AbstractDistributed Artificial Intelligence has been loosely defined in terms of computation by distributed, intelligent agents. Although a variety of projects employing widely ranging methodologies have been reported, work in the field has matured enough to reveal some consensus about its main characteristics and principles. A number of prominent projects are described in detail, and two general frameworks, theSystem conceptual modeland theagent conceptual model, are used to compare the different approaches. The paper concludes by reviewing approaches to formalizing some of the more critical capabilities required by multi-agent interaction.

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