Comparison of Fuzzy Membership Functions for Value of Information Determination Sheng Miao and Robert J. Hammell II Department of Computer and Information Sciences Towson University, Towson, MD USA smiao1@students.towson.edu; rhammell@towson.edu Timothy Hanratty Computational Information Science Directorate US Army Research Laboratory, Aberdeen Proving Ground, MD USA timothy.p.hanratty.civ@mail.mil Ziying Tang Department of Computer and Information Sciences Towson University, Towson, MD USA ztang@towson.edu Abstract Network-centric military operations are redefining information overload as military commanders and staffs are inundated with vast amounts of information. Recent research has developed a fuzzy-based system to assign a Value of Information (VoI) determination for individual pieces of information. This paper presents an investigation on the effect of using triangular and trapezoidal fuzzy membership functions within the system. Introduction Today’s military operations utilize information from a myriad of sources that provide overwhelming amounts of data. A primary challenge of decision makers at all levels is to identify the most important information with respect to the mission at hand, and often do so within a limited amount of time. The process of assigning a Value of Information (VoI) determination to a piece of information has historically been a multi-step, human-intensive exercise requiring intelligence collectors and analysts to make judgments within differing operational situations. Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-11-2-0092. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein. Recently, a fuzzy associative memory architecture was used to develop a system to calculate VoI in complex military environments based on the information’s content, source reliability, latency, and the specific mission context under consideration (Hanratty, Hammell, and Heilman 2011; Hammell, Hanaratty, and Heilman 2012). Military intelligence analysts were used as subject matter experts to provide the fuzzy association rules from which the system was constructed, and preliminary results from the system have been demonstrated and “validated” in principal and context (Hanratty et al. 2012; Hanratty et al. 2013). Efforts are continuing towards a more formal validation of the system and to empirically evaluate the effects of the system on intelligence analyst performance (Newcomb and Hammell 2012; Newcomb and Hammell 2013). This paper presents an investigation on the effect of using two different membership functions within the fuzzy-based system and a comparative analysis of the differences between them. The paper is organized as follows: the next section presents background information on VoI as well as the design of the original fuzzy system. This is followed by a section that discusses the experimental framework used for this work, and then a section describing the experiments and results. The paper concludes with a section that provides conclusions and future work.