Karl Perusich

Fuzzy cognitive maps for policy analysis

Fuzzy cognitive maps are introduced as a way to model state changes in a dynamic system where policy and technological components must be directly compared. To illustrate the process of developing a map and infer state changes from it, an action/reaction arms race of the Richardson type is modeled. Because fuzzy cognitive maps qualitatively capture the essential interactions of a system, numerical predictability of outputs is lost. Instead, the user is gaining a more seemless way to compare information and artifacts that have lack a common numerical measure.

Using Fuzzy Cognitive Maps for Knowledge Management in a Conflict Environment

In modern military battlefield environments, the availability of data and information has increased exponentially. Through information and communications technology, individuals and teams can access real-time data about almost any aspect of their current conflict situation, but this instantaneous availability of information to individuals and teams in these conflict situations does not always result in better or faster decisions. Instead, the speed and volume of data made available through surveillance, monitoring, analysis, computer, and communications technology can quickly overwhelm decision makers. Worse, different decision makers that need to coordinate their actions as part of a team effort might use different filters to reduce their data to something more manageable, or what they perceive as more relevant, to their emerging situation. To better manage the information in real time, a mediator is necessary. Fuzzy cognitive maps are proposed as one possible technique for mediating the information made available to decision makers. Such maps were used as part of a research project that used novice teams to simulate an Airborne Warning and Control System (AWACS) crew managing air assets in a conflict situation. The process of constructing the maps, their role in the simulation, and preliminary results of the test runs of the AWACS simulation are presented

Modeling, measuring, and mediating teamwork: the use of fuzzy cognitive maps and team member schema similarity to enhance BMC/sup 3/I decision making

A research study is reported which utilizes an AWACS based distributed decision making environment to assess: a) team interaction b) a cognitive interface containing team-level cues, c) a cognitive interface with information mediation. The hypothesis suggests that when teams are afforded an interface that suggests increased communications about team member schemas and shared situation awareness (modeled by joint cognitive processes), then team performance will increase. Results show partial support for the hypothesis for the AWACS scenarios tested. The team member schema similarity (TMSS) cues were shown to be a useful component in team effectiveness. Conclusions suggest how this research can be extended and utilized for developing cognitive interfaces and collaborative computing systems that produce shared situation awareness in complex settings.

Advancing Socio-Technical Systems Design Via the Living Laboratory

The natural, living world provides the backdrop for the practice of participatory ergonomics. By addressing the salient issues of complexity, context, distributed cognition, and team situational awareness in this world, the advocation of the Living Laboratory concept is presented. Socio-technical systems design is reflected through the joint integration of various Living-Lab outcomes such as Fields of practice, tools, technologies, qualitative models, scaled worlds, and in situ evaluations. A wholistic approach is derived by looking at these outcomes as a basis to bind together the cognitive, social, technological, and organizational constraints that design must consider to be effective.

Assessing teamwork for accreditation: Understanding what needs to be known and its integration into engineering and technology curricula

Most future engineering and technology graduates will work on complex projects in a team environment requiring multiple skill sets. These are critical skills that the future engineer must acquire to readily adapt to the global work environment. Assessing effective teamwork skills as part of the ABET process is very important. To effectively assess how teams work, categorization of skills and an understanding of why engineers and technologists must work in teams is a necessity. In addition, peculiarities, which might exist with teamwork in a technical setting and often differentiating from teamwork in other contexts, must be identified. With such a categorization, a skill set can be defined and used as a template for incorporation into engineering and technology curricula. This template will serve as a guide for understanding and assessing necessary teamwork skills. Key characteristics, such as time, complexity and knowledge limitations that generally require technical personnel to work as a team to complete a task will be enumerated and the nature of technical teamwork defined. This can be used to define the capabilities an engineer needs to be an effective working team member. These capabilities have associated skill sets that translate in the various knowledge bases that can be incorporated into engineering curricula and become a template for assessing teamwork in an engineering program.

Qualitative modeling of complex systems for cognitive engineering

In this paper, the techniques of using fuzzy cognitive maps will be outlined, and demonstrated with an example. Fuzzy cognitive maps will be used as a way to model the causal process in a cognitive system. With such a model interventions to change the dynamics of the system can be developed. In the particular example, the information on a display needed to be improved to support group situation awareness within an AWACS team. A fuzzy cognitive map was developed of the chain of causality that led from the current information structure of the AWACS display to the loss of situation awareness. The map could then be examined to identify ways in which the linkages could be altered to improve situation awareness, and points at which technology could be applied. From this a set of design changes could be recommended.

Using fuzzy cognitive maps as an intelligent analyst

With the increasing sources and volume of data available to an analyst, the development of decision aids is increasingly necessary to filter and format it for use by intelligence analysts. In this paper the use of fuzzy cognitive maps as such a filter will be described. The technique will be incorporated as a decision aid in Neocities; a dynamic simulation used to investigate the technology is used by teams to communicate and coordinate their actions

What is Command and Control Coming to? Examining Socio-Cognitive Mediators That Expand the Common Ground of Teamwork

The design of command and control centers has undergone significant changes in recent years. In contrast to traditional human factors, contemporary approaches to the design of future command posts will necessarily engage various socio-cognitive activities that lead to effective and efficient teamwork. This paper provides a description of the contemporary “Living Lab” approach and the presentation of a study involving the use of socio-cognitive mediators within a simulated command post environment. The roles and outcomes of team member schema similarity and fuzzy cognitive maps (as two distinct types of mediators) are presented along with their use in a complex, situated problem domain involving AWACS command and control operators. Implications are drawn that suggest how socio-cognitive mediators may be used to expand and understand the common ground of teamwork and how this applies to the envisioned design of command and control centers.

Qualitatively troubleshooting electronic circuits using fuzzy cognitive maps

Fuzzy cognitive maps are used as a qualitative modeling technique for troubleshooting electronic circuits. Because they compare states to states, a trade off exists in their use. Qualitative evaluation is substituted for complexity. The map qualitatively evaluates how changes in underlying concepts represented by its nodes cause changes in other concepts represented by other nodes. Evaluation of a set of possible causes in a map can be done in two ways. In the first, nodal changes are applied to a set of nodes and the causality propagated through to output nodes of interest. In the second a reachability matrix can be construct red to identify which nodes can in fact affect the output node. Other nodes are then eliminated from further evaluation. Fuzzy cognitive maps have several potential advantages. The system map can be constructed by piecing together submaps individually constructed. Because changes in state are compared to changes in state inferring output nodal values, a common numeric metric is not necessary when incorporating different concepts.

Information warfare: radar in World War II as an historical example

Emerging technologies have increased the capability to acquire and use data as a weapon in warfare. Although aggregated under a common term, information warfare actually represents a variety of different ways with different actors in different environments that information can be used as part of an arsenal. One important form of information warfare is decision making (or OODA-loop) warfare, in which a defender or attacker uses information acquisition or processing technology to complete their decision making cycle quicker than an opponent can to maintain the initiative in the battle. Such a type of information warfare was used during the Battle of Britain in World War 2. Radar was an enabling technology that gave Great Britain an edge in the decision making process that contributed to Englands ultimate victory in the battle.