Active mechanism of deceit detection for multi-agent based interaction

Abstract

Unlike traditional detection methods, which are essentially a passive approach, this paper presents a novel approach active deceit detection (ADD) against the deception problem in multi-agent interaction. ADD does not only receive and process the communicative messages, but also proactively interact to environment and interacted agents via negotiation to explore evidence for further detection. It makes detection become an active process to ensure secure collaborations in open environment. This paper presents the definition of the active deceit detection model and gives a theoretical analysis of its property on it. Moreover, an ideal estimate model of ADD, called ideal oscillation model and throw-stone test, is also further discussed.