A Realistic Dataset for the Smart Home Device Scheduling Problem for DCOPs

William Kluegel, Muhammad A. Iqbal, Ferdinando Fioretto, William Yeoh, Enrico Pontelli

Research output: Chapter in Book/Entry/PoemConference contribution

6 Scopus citations

Abstract

The field of Distributed Constraint Optimization has gained momentum in recent years thanks to its ability to address various applications related to multi-agent cooperation. While techniques for solving Distributed Constraint Optimization Problems (DCOPs) are abundant and have matured substantially since the field’s inception, the number of DCOP realistic applications available to assess the performance of DCOP algorithms is lagging behind. To contrast this background we (i) introduce the Smart Home Device Scheduling (SHDS) problem, which describes the problem of coordinating smart devices schedules across multiple homes as a multi-agent system, (ii) detail the physical models adopted to simulate smart sensors, smart actuators, and homes’ environments, and (iii) introduce a realistic benchmark for SHDS problems.

Original languageEnglish (US)
Title of host publicationAutonomous Agents and Multiagent Systems - AAMAS 2017 Workshops, Visionary Papers, Revised Selected Papers
EditorsGita Sukthankar, Juan A. Rodriguez-Aguilar
PublisherSpringer Verlag
Pages125-142
Number of pages18
ISBN (Print)9783319716787
DOIs
StatePublished - 2017
Externally publishedYes
Event16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017 - Sao Paulo, Brazil
Duration: May 8 2017May 12 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10643 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017
Country/TerritoryBrazil
CitySao Paulo
Period5/8/175/12/17

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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