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Non-monotonic reasoning rules for energy efficiency

Authors: TOMAZZOLI, Claudio; CRISTANI, Matteo; KARAFILI, Erisa; OLIVIERI, FRANCESCO;

Non-monotonic reasoning rules for energy efficiency

Abstract

Conflicting rules and rules with exceptions are very common in natural language specification employed to describe the behaviour of devices operating in a real-world context. This is common exactly because those specifications are processed by humans, and humans apply common sense and strategic reasoning about those rules to resolve the conflicts. In this paper, we deal with the challenge of providing, step by step, a model of energy saving rule specification and processing methods that are used to reduce the consumptions of a system of devices, by preventing energy waste. We argue that a very promising non-monotonic approach to such a problem can lie upon Defeasible Logic, following therefore an approach that has shown success in the current literature about usage of this logic for conflict rule resolution and for human–computer interaction in complex systems. Starting with rules specified at an abstract level, but compatibly with the natural aspects of such a specification (including temporal and power absorption constraints), we provide a formalism that generates the extension of a basic Defeasible Logic, which corresponds to turned on or off devices.

Countries
Italy, United Kingdom
Keywords

Artificial intelligence, Technology, Defeasible logic, 0805 Distributed Computing, Energy conservation, Ambient intelligence techniques, Computer Science, Artificial Intelligence, Automatic reasoning, Artificial Intelligence, AMBIENT-INTELLIGENCE, Intelligent systems, intelligent systems, ENVIRONMENT, Science & Technology, Computer Science, Information Systems, BUILDINGS, knowledge representation, Distributed computing and systems software, CONSUMPTION, 004, defeasible logic, Energy efficiency, OPTICAL IP NETWORKS, Knowledge representation, Computer Science, Telecommunications, Ambient intelligence, Human computer interaction, automatic reasoning, Information Systems

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Average
Top 10%
Top 10%
Green
bronze