WSC 2005

WSC 2005 Final Abstracts

Agent Based Modeling Track

Monday 1:30:00 PM 3:00:00 PM
New Approaches to Agent Based Modeling

Chair: Arnold Buss (Naval Postgraduate School)

Developing an Agent Model of Human Performance in Air Traffic Control Operations Using Apex Cognitive Architecture
Seung Man Lee, Ujwala Ravinder, and James C. Johnston (NASA Ames Research Center)

For the analysis of large-scale complex systems, agent-based modeling and simulation has proven to provide a valuable research tool. The emphasis has, however, typically been on representing the dynamic behavior of physical entities such as aircraft. Simulation of human operators has often been minimal even though human behavior has an enormous impact on overall system performance and safety. Therefore, human capabilities and limitations need to be taken into account early in the system design process before irrevocable choices have been made. This paper reports on the development of agent models with human-like performance characteristics using a cognitive architecture. We present an agent model of an air traffic controller that is developed and incorporated into an agent-based simulation of the national airspace to support the design and evaluation of advanced air transportation concepts.

Modeling Force Response to Small Boat Attack Against High Value Commercial Ships
David J. Walton (US Navy Department Head School) and Eugene P. Paulo, Christopher J. McCarthy, and Ravi Vaidyanathan (Naval Postgraduate School)

This study examines ways to prevent the success of a small boat terrorist attack (SBA) against a larger high value commercial vessel, or high value unit (HVU), through the utilization of an agent-based simulation. The geographic area of concern is the Straits of Malacca. An essential element of the scenario is the limited time available to act against the attackers. Subsequently, the two alternatives considered are the deployment of patrol craft, as well as the placement of well-armed Sea Marshals on each high value ship.

Simple Movement and Detection in Discrete Event Simulation
Arnold H. Buss and Paul J. Sanchez (Naval Postgraduate School)

Many scenarios involving simulation require modeling movement and sensing. Traditionally, this has been done in a time-stepped manner, often because of a mistaken belief that using a pure discrete event approach is infeasible. This paper discusses how simple motion (linear, uniform, two-dimensional) and simple sensing can be modeled with a pure Discrete Event approach. We demonstrate that this approach is not only feasible, it is often more desirable from several standpoints.

Monday 3:30:00 PM 5:00:00 PM
Agent Applications of Coevolutionary Dynamics

Chair: Paul Sanchez (Naval Post Graduate School)

Leveraging Agent Based Simulation for Rapid Course of Action Development
Philip S. Barry and Matthew T. K. Koehler (The MITRE Corporation)

In the spring of 2005 a limited objective experiment was carried out to assess the feasibility of using agent based simulations to enhance co-evolutionary course of action development. In particular, relatively low fidelity simulations were employed to visualize the results of particular courses of action. Over four days multiple courses of action were developed by two opposing teams with similar force structures and then run against one another in an agent based modeling environment to test their ability to achieve the given mission. The results of the experiment indicate that there is significant potential for low fidelity simulations to stimulate objective thinking in course of action development.

Investigating the Dynamics of Competition: Coevolving Red and Blue Simulation Parameters
Mary L. McDonald (George Mason University) and Stephen C. Upton (Referentia Systems, Inc.)

In this paper we explore the concept of two-sided competitive coevolution as a mechanism to explore the dynamics of competition in a simulation context. One potential value of doing so is the ability to rapidly explore simultaneous adaptations to two sides, presumably Blue and Red, in order to find solutions that perform well and are relatively robust even in the face of an adaptive adversary.

Coevolutionary Dynamics and Agent-based Models in Organization Science
Brian F. Tivnan (Executive Leadership Doctoral Program)

This paper provides empirical and theoretical support for the application of coevolutionary dynamics and agent-based models in organization science. The support stems from the following logical progression: (a) organization science theorists have explored, and in many instances, acknowledged the applicability of complexity theory to organization science research; (b) much of the acceptance for complexity science applications follows from the conceptualization of an organization as a Complex Adaptive System (CAS); (c) complexity science offers a robust explanation of order in natural and social systems; (d) coevolutionary dynamics provide the mechanisms with the highest explanatory power for describing order-creation in social systems. This paper provides an overview of the literature for each element of the preceding logical progression and concludes with a discussion of the applications of agent-based models to instantiate coevolutionary dynamics.

Tuesday 8:30:00 AM 10:00:00 AM
Agent Based Modeling

Chair: Rainer Dronzek (Automation Associates, Inc.)

Performance Evaluation of Agent-based Material Handling Systems Using Simulation Techniques
Radu F. Babiceanu and F. Frank Chen (Virginia Polytechnic Institute and State University)

The increasing influence of global economy is changing the conventional approach to managing manufacturing companies. Real-time reaction to changes in shop-floor operations, quick and quality response in satisfying customer requests, and reconfigurability in both hardware equipment and software modules, are already viewed as essential characteristics for next generation manufacturing systems. Part of a larger research that employs agent-based modeling techniques in manufacturing planning and control, this work proposes an agent-based material handling system and contrasts the centralized and decentralized scheduling approaches for allocation of material handling operations to the available resources in the system. To justify the use of the decentralized agent-based approach and assess its performance compared to conventional scheduling systems, a series of validation tests and a simulation study are carried out. As illustrated by the preliminary results obtained in the simulation study the decentralized agent-based approach can give good feasible solutions in a short amount of time.

Integrating Agent Based Modeling Into a Discrete Event Simulation'
Benjamin Joseph Dubiel and Omer Tsimhoni (The University of Michigan)

Movement of entities in discrete event simulation typically requires predefined paths with decision points that dictate entity movement. Human-like travel is difficult to model correctly with these constraints because that is not how people move and large individual differences exist in capabilities and strategies. Agent based modeling is considered a better way to simulate the real-time interaction of people with their environment. In this paper we propose to integrate agent based modeling with discrete event simulation to simulate the movement of people in a discrete event system. An agent based module was constructed within the AutoMod simulation package, and a test case was modeled in which people (agents) at a theme-park interact with objects and people in their environment to get directions and then walk or take a tram to their final destination. We explain the details of model implementation and describe the verification and initial validation of the model.

Argus Invasive Species Spread Model Constructed Using Agent-based Modeling Approach and Cellular Automata
S. Clifton Parks (AgriLogic, Inc.), Maxim Garifullin (XJ Technologies) and Rainer Dronzek (Automation Associates, Inc.)

The stochastic Argus Invasive Species Spread Model (AISSM) is constructed using an Agent-Based Modeling (ABM) approach with cellular automata (CA) to account for spatial relationships and changes in those relationships over time. The model was constructed to support a wide range of geographical locations; however, this paper focuses on its application in the state of California. A time-series of daily historical weather observations on a 6-kilometer grid was obtained for six weather variables important to insect and disease development. Weather conditions were then simulated using the K- nearest neighbor (K-nn) regional weather generator. The weather simulations were summarized into a monthly time-step and coupled with satellite land cover imagery to identify a habitat quality for each simulated month. This information was combined with the introduction of invasive species in the AnyLogic™ modeling environment. The spread of invasive species is driven by the habitat quality layer, which regulates its dispersal rate.

Tuesday 10:30:00 AM 12:00:00 PM
Agent-based Simulation in AI Planning

Chair: Paul Sanchez (Naval Post Graduate School)

Simulating Users to Support the Design of Activity Management Systems
Julie S. Weber and Martha E. Pollack (University of Michigan)

We describe a simulation system that models the user of a calendar-management tool. The tool is intended to learn the user's scheduling preferences, and we employ the simulator to evaluate learning strategies. The simulated user is instantiated with a set of preferences over local and global features of a schedule such as the level of importance of a particular meeting and the amount of preparation time available before it is to begin. The system then processes a set of simulated meeting requests, and over time and through user feedback, it learns the user's preferences, affording it the ability to thereafter manage the user's schedule more autonomously.

Simulation-based Planning for Planetary Rover Experiments
David Joslin (Seattle University) and Jeremy Frank, Ari K. Jónsson, and David Smith (Intelligent Systems Division)

Time and resource limitations mean that current Mars rovers (and any future planetary rovers) cannot hope to achieve every desirable scientific goal. We must therefore select and plan for a subset of the possible experiments, maximizing some utility metric. The use of simulation in planning is appealing because of its potential for representing complex, realistic details about the rover and its environment. We demonstrate a planning algorithm that performs high-level planning in a space of plan strategies, rather than actual plans. In the current implementation, candidate strategies are evaluated by a simple simulation, and a genetic algorithm is used to search for effective strategies. Preliminary results are encouraging, particularly the potential for modeling uncertainty about the time required to complete actions, and the ability to develop strategies that can deal with this uncertainty gracefully.

Agent-based Simulation for Software Project Planning
David Joslin and William Poole (Seattle University)

Estimates of task duration and resource requirements in software engineering are notoriously inaccurate, and as a result effective project management often must be very dynamic. In response to new information or revised estimates, it may be necessary to reassign resources, cancel optional tasks, etc. Project management tools that make projections while treating decisions about tasks and resource assignments as static will not yield realistic results. In this paper we describe some preliminary attempts to adapt a simulation-based planning algorithm developed for planning experimental activities of Mars rovers to the problem of planning for software project management. Simulation techniques offer the potential for modeling the way agents behave in project development, and the way a manager might adapt the project plan based on the project status at future points, resulting in a tool that more accurately reflects the realities of software project management.