Recently, modeling of decision making and control systems that include heterogeneous
smart sensing devices (machines) as well as human agents as participants is becoming an …

In critical environments that require a high accuracy of decisions, utilizing human cognitive
strengths and expertise in addition to machine observations is advantageous to improve …

This paper establishes a mathematical framework to analyze the behavioral utility-based
distributed detection problem for 𝑀-ary hypothesis testing with conditionally independent …

Due to the difficulty of decentralized inference with conditional dependent observations, and
motivated by large-scale heterogeneous networks, we formulate a framework for …

This work considers a Bayesian signal processing problem where increasing the power of
the probing signal may cause risks or undesired consequences. We employ a market based …

This paper introduces a representative-based approach for distributed learning that
transforms multiple raw data points into a virtual representation. Unlike traditional distributed …

In this work, we consider a binary hypothesis testing problem involving human decision-
makers. Due to the nature of human behavior, human decision-makers observe the …

This paper presents a novel cyber deception technique that can employ fake nodes to
deceive attackers. To devise such a technique, the paper uses game theory to model …

This paper proposes a belief-updating scheme in a human-machine collaborative decision-
making network to com-bat Byzantine attacks. A hierarchical framework is used to realize the …

Analytical Hierarchy Processing (AHP) assists in estimation of input-specific weights for
improving system-level decision making operations. The process initially decides a goal …