A Realistic Dataset for the Smart Home Device Scheduling Problem for DCOPs
This addresses a gap in DCOP research by offering a practical benchmark for researchers, though it is incremental as it builds on existing DCOP methods without proposing new algorithms.
The authors tackled the lack of realistic benchmarks in Distributed Constraint Optimization (DCOP) by introducing the Smart Home Device Scheduling (SHDS) problem and a corresponding realistic dataset, providing a new benchmark for evaluating DCOP algorithms in multi-agent smart home coordination.
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.