Walter Warwick

Adaptive learning typically focuses on the challenge of adjusting the presentation of instructional material based on an automated assessment of real-time student performance. The goal is to move away from a one-size-fits-all approach to learning toward a more personalized experience. While we support this goal, in this paper we focus on a related...

There is an unspoken but pervasive assumption that the human behavior representations which populate simulation-based training systems must exhibit realistic behavior if the training is to be effective. This assumption motivates the continual calls to improve the realism of computer-generated forces and reflects the concern that human behavior repr...

Agent-based models are commonplace in the simulation-based analysis of cyber security. But as useful as it is to model, for example, adversarial tactics in a simulated cyber attack or realistic traffic in a study of network vulnerability, it is increasingly clear that human error is one of the greatest threats to cyber security. From this perspecti...

Historically, cognitive modeling has been an exercise in theory confirmation. “Cognitive architectures” were advanced as computational instantiations of theories that could be used to model various aspects of cognition and then be put to empirical test by comparing the simulation-based predictions of the model against the actual performance of huma...

The history of agent development is a litany of expensive one-off solutions that are opaque to the uninitiated, difficult to maintain and impossible to re-use in novel contexts. This outcome is the unfortunate result of a tendency to apply monolithic “architectures” to agent development, which require specialists to build the models and extensive k...

The development of a human performance model is an exercise in complexity. Despite this, techniques that are commonplace in the study of complex dynamical systems have yet to find their way into human performance modeler’s toolbox. In this paper, we describe our efforts to develop new generative and analytical methods within a task network modeling...

The modeling and simulation of human performance forces the analyst to confront a range of well-known but difficult challenges. One challenge the analyst does not seem to face is a shortage of human performance modeling tools. But because there is no uniform framework for expressing the content and structure of a human performance model, it is diff...

In this paper we present a model of the prisoner's dilemma in which human-like, adversarial behaviors emerge from interactions between two naturalistic models. In the prisoner's dilemma, like other simple two-player games, the behaviors that arises from iterated play can be surprisingly complex. We developed a model of this task using an integrated...

The Graph-Based Interface Language (GRBIL) tool combines aspects of virtual and constructive simulations. GRBIL can be used to set up a virtual simulation where people can interact with a simulation of an operator interface and environment. Human-in-the-loop activity can be recorded when a person performs a procedure with the simulated interface. T...

Metacognition and Multiple Strategies in a Cognitive Model of Online Control We present a cognitive model performing the Dynamic Stocks&Flows control task, in which subjects control a system by counteracting a systematically changing external variable. The model uses a metacognitive layer that chooses a task strategy drawn from of two classes of st...

Cognitive Science and Artificial Intelligence share compatible goals of understanding and possibly generating broadly intelligent behavior. In order to determine if progress is made, it is essential to be able to evaluate the behavior of complex computational models, especially those built on general cognitive architectures, and compare it to bench...

As organizations continue to evolve and integrate even more advanced information technology capabilities, traditional cognitive models of human performance, both at the individual and team level, must similarly mature in order to flexibly adapt to the challenges faced by teams performing in today's complex operational environments. The overall goal...

Using the MS/RPD integrated modeling approach, we have modeled a variety of tasks. We typically try to capture aspects of human performance and evaluate the qualitative and quantitative fit of model behavior to human data. A collection of individual models and demonstrations of fit to human data constitute an important validation of a modeling appr...

At present, no single tool or analytical technique can analyze and account for the wide range of data and contexts in complex networked environments. This paper describes an ongoing collaborative effort of Pearson’s Knowledge Technologies (PKT) division, Carnegie Mellon University’s Center for the Computational Analysis of Social and Organizational...

We investigate the relationship between two approaches to modeling physical systems. On the first approach, simplifying assumptions are made about the level of detail we choose to represent in a computational simulation with an eye toward tractability. On the second approach simpler, analogue physical systems are considered that have more or less w...

We contrasted and compared independently developed computational models of human performance in a common dynamic decision-making task. The task, called dynamic stocks and flows, is simple and tractable enough for laboratory experiments yet exhibits many characteristics of macrocognition. A macrocognitive model was developed using a computational in...

The evaluation of an AGI system can take many forms. There is a long tradition in Artificial Intelligence (AI) of competitions focused on key challenges. A similar, but less celebrated trend has emerged in computational cognitive modeling, that of model comparison. As with AI competitions, model comparisons invite the development of different compu...

Task network modeling is a powerful computational modeling tool that supports the analysis of complex systems, but it is perceived to lack cognitive fidelity. We describe an approach for adding fidelity to task network models, using a simple "naturalistic" mechanism based on multiple trace memory and reinforcement-like learning. We present a model...

Report developed under Small Business Innovation Research contract. Where human behavior is often thought of in terms of a perception-action cycle, rich with interdependencies and fuzzy boundaries between processes, human behavior representations of a computer-generated force implement a one-way process where exact, unambiguous data drive discrete,...

Computational models of cognition are most often developed to explore or vindicate particular theoretical views in psychology. The computer provides a ready environment in which to develop models and generate quantitative predictions about cognitive performance which, in turn, can be compared against actual human performance. Validating the model w...

The philosopher of science Gustav Hempel famously argued for the symmetry of prediction and explanation in scientific practice. Pointing to parallels in their logical structure, Hempel maintained that any adequate scientific explanation could engender a prediction, and vice versa. This symmetry is evident in the practice of computational cognitive...

In this paper we describe techniques we have adopted to develop a computer-based, outcome-driven simulator to train digital information skills for small unit leaders of the Army's Future Force Warrior program. We begin by contrasting attempts to engender ?virtual realism? in simulation based training against attempts to engender cognitive realism b...

Modeling an intelligent adversary has provided great challenges to simulated training realism. Traditional approaches to modeling have relied on rule-based and analytical decision-making models in an attempt to optimize the decision making of an intelligent computer-generated adversary. In order to promote realistic transfer of training in the real...

In this paper we describe our ongoing work to develop a computational representation of Klein’s model of Recognition-Primed Decision making (RPD). The RPD model differs from traditional, analytical models of decision making insofar as RPD emphasizes situation assessment rather than the comparison of options. Like many efforts, our research is motiv...

In May 2000, Micro Analysis and Design, Inc. and Klein Associates, Inc., were awarded a Phase 1 SBIR to research and develop computational models of decision making in stressful and uncertain conditions (Topic #N00-074, Modeling and Simulation of Decision-making Under Uncertainty). This research was motivated by the need for improved behavioral rea...

This paper describes a series of efforts to integrate a cognitive modeling architecture (ACT-R) with a task network simulation tool (IMPRINT). The goal is to combine the advantages of both approaches while minimizing their shortcomings. We describe a number of applications in which different ways of combining the two systems are attempted. The bene...

In this paper we describe three ongoing projects intended to improve the representation of human decision-making in military simulations. Each project addresses a different aspect of decision making. The first project extends the functionality of the Improved Performance Research Integration Tool (IMPRINT) by allowing the user to create a detailed...

Over the past several years, we have developed and tested a computational implementation of recognition-primed decision making (RPD) within Micro Saint Sharp task network models. The goal of this work was to augment task network models to improve their cognitive fidelity and flexibility. Our RPD mechanism uses multiple trace memory with a simple re...

1. Background At the 2008 BRIMS conference, we introduced the Human Behavior Architecture (Warwick et al., 2008). The HBA is the culmination of several efforts to integrate task network and cognitive modeling within a unified development and simulation environment (Lebiere et al, 2002; Lebiere, Archer, Warwick and Schunk, 2005; Lebiere, Best, Arche...