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

## TL;DR

This paper introduces a realistic dataset and benchmark for the Smart Home Device Scheduling problem within the DCOP framework, addressing the gap in practical applications and evaluation tools for multi-agent smart home coordination.

## Contribution

It presents the SHDS problem, detailed physical models for smart home components, and a new benchmark dataset for evaluating DCOP algorithms in realistic smart home scenarios.

## Key findings

- First realistic benchmark for SHDS in DCOPs
- Enhanced simulation models for smart sensors and actuators
- Facilitates performance assessment of DCOP algorithms in practical settings

## 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 to solve Distributed Constraint Optimization Problems (DCOPs) are abundant and have matured substantially since the field inception, the number of DCOP realistic applications and benchmark used to asses the performance of DCOP algorithms is lagging behind. To contrast this background we (i) introduce the Smart Home Device Scheduling (SHDS) problem, which describe 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 DCOP realistic benchmark for SHDS problems.