OUTLINE Introduction to Simulation Definitions. Defines simulation, its applications, and the benefits derived from using the technology. Compares simulation to related activities in analysis and gaming. DOD Overview.  Explains the simulation perspective and categorization of the US Department of Defense.  Training, Analysis, and Gaming.  Provides a general delineation between these three categories of simulation.  System Architectures Components. Describes the fundamental components that are found in most military simulations.  Designs. Describes the basic differences between functional and object oriented designs for a simulation system.  Infrastructures.  Emphasizes the importance of providing an infrastructure to support all simulation models, tools, and functionality.  Frameworks.  Describes the newest implementation of an infrastructure in the form of an object oriented framework from which simulation capability is inherited.  Interoperability Dedicated.  Interoperability initially meant constructing a dedicated method for joining two simulations for a specific purpose.  DIS. The virtual simulation community developed this method to allow vehicle simulators to interact in a small, consistent battlefield. ALSP.  The constructive, staff training community developed this method to allow specific simulation systems to interact with each other in a single joint training exercise.  HLA.  This program was developed to replace and, to a degree, unify the virtual and constructive efforts at interoperability.  Event Management Queuing. The primary method for executing simulations has been various forms of queues for ordering and releasing combat events.  Trees. Basic queues are being supplanted by techniques such as Red-Black and Splay trees which allow the simulation store, process, and review events more efficiently than their predecessors.  Event Ownership.  Events can be owned and processed in different ways. Today's preference for object oriented representations leads to vehicle and unit ownership of events, rather than the previous techniques of managing them from a central executive.  Time Management Universal. Single processor simulations made use of a single clocking mechanism to control all events in a simulation.  This was extended to the idea of a "master clock" during initial distributed simulations, but is being replaced with more advanced techniques in current distributed simulation.  Synchronization. The "master clock" too often lead to poor performance and required a great deal of cross-simulation data exchange.  Researchers in the Parallel Distributed Simulation community provided several techniques that are being used in today's training environment.  Conservative & Optimistic. The most notable time management techniques are conservative synchronization developed by Chandy, Misra, and Bryant, and optimistic synchronization (or Time Warp) developed by David Jefferson.  Real-time. In addition to being synchronized across a distributed computing environment, many of today's simulators must also perform as real-time systems.  These operate under the additional duress of staying synchronized with the human or system clock perception of time.  Physical Modeling Object Interaction. Military object modeling is be divided into two pieces, the physical and the behavioral.  Object interactions, which are often viewed as 'physics based', characterize the physical models. Movement. Military objects are often very mobile and a great deal of effort can be given to the correct movement of ground, air, sea, and space vehicles across different forms of terrain or through various forms of ether.  Sensor Detection. Military object are also very eager to interact with each other in both peaceful and violent ways.  But, before they can do this they must be able to perceive each other through the use of human and mechanical sensors.  Engagement. Encounters with objects of a different affiliation often require the application of combat engagement algorithms.  There are a rich set of these available to the modeler, and new ones are continually being created.  Attrition. Object and unit attrition may be synonymous with engagement in the real world, but when implemented in a computer environment they must be separated to allow fair combat exchanges.  Distributed simulation systems are more closely replicating real world activities than did their older functional/sequential ancestors, but the distinction between engagement and attrition are still important.  Communication. The modern battlefield is characterized as much by communication and information exchange as it is by movement and engagement.  This dimension of the battlefield has been largely ignored in previous simulations, but is being addressed in the new systems under development today.  More. Activities on the battlefield are extremely rich and varied.  The models described in this section represent some of the most fundamental and important, but they are only a small fraction of the detail that can be included in a model.  Behavioral Modeling Perception.  Military simulations have historically included very crude representations of human and group decision making.  One of the first real needs for representing the human in the model was to create a unique perception of the battlefield for each group, unit, or individual.  Reaction. Battlefield objects or units need to be able to react realistically to various combat environments.  These allow the simulation to handle many situations without the explicit intervention of a human operator.  Planning. Today we look for intelligent behavior from simulated objects.  Once form of intelligence is found in allowing models to plan the details of a general operational combat order, or to formulate a method for extracting itself for a difficult situation.  Learning. Early reactive and planning models did not include the capability to learn from experience.  Algorithms can be built which allow units to become more effective as they become more experienced. They also learn the best methods for operating on a specific battlefield or under specific conditions.  Artificial Intelligence. Behavioral modeling can benefit from the research and experience of the AI community.  Techniques of value include: Intelligent Agents, Finite State Machines, Petri Nets, Expert and Knowledge-based Systems, Case Based Reasoning, Genetic Algorithms, Neural Networks, Constraint Satisfaction, Fuzzy Logic, and Adaptive Behavior.  An introduction is given to each of these along with potential applications in the military environment.  Environmental Modeling Terrain. Military objects are heavily dependent upon the environment in which they operate.  The representation of terrain has been of primary concern because of its importance and the difficulty of managing the amount of data required.  Triangulated Irregular Networks (TINs) are one of the newer techniques for managing this problem.  Atmosphere. The atmosphere plays an important role in modeling air, space, and electronic warfare.  The effects of cloud cover, precipitation, daylight, ambient noise, electronic jamming, temperature, and wind can all have significant effects on battlefield activities.  Sea. The surface of the ocean is nearly as important to naval operations as is terrain to army operations. Sub-surface and ocean floor representations are also essential for submarine warfare and the employment of SONAR for vehicle detection and engagement.  Standards. Many representations of all of these environments have been developed.  Unfortunately, not all of these have been compatible and significant effort is being given to a common standard for supporting all simulations. Synthetic Environment Data Representation and Interchange Specification (SEDRIS) is the most prominent of these standardization efforts.  Multi-Resolution Modeling Aggregation. Military commanders have always dealt with the battlefield in an aggregate form.  This has carried forward into simulations which operate at this same level, omitting many of the details of specific battlefield objects and events.  Disaggregation. Recent efforts to join constructive and virtual simulations have required the implementation of techniques for cross the boundary between these two levels of representation.  Disaggregation attempts to generate an entity level representation from the aggregate level by adding information.  Conversely, aggregation attempts to create the constructive from the virtual by removing information.  Interoperability. It is commonly accepted that interoperability in these situations is best achieved though disaggregation to the lowest level of representation of the models involved. In any form the patchwork battlefield seldom supports the same level of interoperability across model levels as is found within models at the same level of resolution.  Inevitability. Models are abstractions of the real world generated to address a specific problem.  Since all problems are not defined at the same level of physical representation, the models built to address them will be at different levels.  The modeling an simulation problem domain is too rich to ever expect all models to operate at the same level.  Multi-Resolution Modeling and techniques to provide interoperability among them are inevitable.  Verification, Validation, and Accreditation  Verification. Simulation systems and the models within them are conceptual representations of the real world.  By their very nature these models are partially accurate and partially inaccurate.  Therefore, it is essential that we be able to verify that the model constructed accurately represents the important parts of the real world we are try to study or emulate.  Validation. The conceptual model of the real world is converted into a software program.  This conversion has the potential to introduce errors or inaccurately represent the conceptual model.  Validation ensures that the software program accurately reflects the conceptual model. Accreditation. Since all models only partially represent the real world, they all have limited application for training and analysis.  Accreditation defines the domains and conditions under which a particular model can be reliably used. VV&A Principles.  The Department of Defense has established specific guidelines for conducting VV&A.  Simulation researchers have also defined fundamental principles that are important for this activity.