A Probabilistic Multi-Agent System Architecture for Reasoning in Smart Homes

Uncertainty is inevitable in ambient assisted living (AAL) environments as sensors may read inaccurate data or due to the existence of unobserved variables for privacy reasons. Furthermore, the dynamic nature of the home environment and vague human communications may result in ambiguous, incomplete and inconsistent contextual information, which ultimately lead the smart home system into uncertainty. This paper aims to tackle some of these challenges, in particular, uncertainty due to vague human communication and missing information in ambient environments. For this, we proposed a probabilistic multi-agent system architecture for reasoning in smart homes by utilizing the notion of multiagent systems (MAS) technologies and probabilistic logic programming techniques. Accordingly, this study shows how the probabilistic reasoning technique enables the agents to reason under uncertainty. Furthermore, it discusses how the intelligent agents enhance their decision-making process by exchanging information about missing data or unobservable variables using agent interaction protocols. In general, the study demonstrates that the combination of MAS technologies and probabilistic logic programming can help in building a reasoning system, which is capable of performing well under vague inhabitant commands and missing information in a partially observable environment.