A context-aware multi-agent reasoning based intelligent assistive formalism

Abstract

In recent years, the rapid proliferation of intelligent smart resource-bounded devices and autonomous software technologies has significantly influenced human life and made human life much smarter, more efficient, flexible, comfortable, and secure but device dependent. These intelligent devices are equipped with the feature of context awareness that often run in a highly decentralized environment with minimal and/or without human intervention. As these systems are often distributed in nature, they exhibit complex adaptive behavior by exchanging contextualized information among different resource-bounded devices and/or systems. However, due to the limitation of resources (computational memory), there are still many challenges for a real-time deployment. In this paper, we present a resource-bounded multi-agent reasoning-based context-aware model that assists users intelligently to take the right action autonomously whenever and wherever needed. The core emphasis is given to the lightweight, efficient reasoning mechanism to manipulate rapidly triggering contextual information with the least utilization of computational resources. We develop algorithms along with the complexity factors to evaluate the system’s efficacy in computational time and memory utilization. To suitably formalize the specification and model the proposed formalism using UPPAAL model checker, we develop the case study of a context-aware intelligent assistant along with its rule-based reasoning strategies and priorities for the execution of prioritized tasks according to the customized needs of the user and verify the correctness properties.