A methodology for applying simulation technologies in the mission operational environment

Surdu, John R.; Pooch, Udo W.

doi:10.1109/it.1998.713378

Cited by 5 publications

(4 citation statements)

References 5 publications

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“…The use of Symbiotic Simulation in management of a semiconductor assembly and test facility has been studied in [6]. The use of Symbiotic Simulation in model-building for social sciences is discussed in [7].…”

Section: C2 Decision Support System Based On Symbiotic Simulationmentioning

confidence: 99%

C2 decision support system based on Symbiotic Simulation

Zhou

Ke-di

2008

2008 Asia Simulation Conference - 7th International Conference on System Simulation and Scientific Computing

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Symbiotic Simulation Systems have been proposed as a new paradigm for discrete event simulation by having simulation and physical system interact in a mutually beneficial manner. Traditional C2 decision support system is analyzed, and the idea of Symbiotic Simulation is introduced. Then the conceptual framework of C2 decision support system based on Symbiotic Simulation is proposed. Each function of the various components of the system is discussed in detail respectively.

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Section: C2 Decision Support System Based On Symbiotic Simulationmentioning

confidence: 99%

C2 decision support system based on Symbiotic Simulation

Zhou

Ke-di

2008

2008 Asia Simulation Conference - 7th International Conference on System Simulation and Scientific Computing

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“…To address these needs, an object permanence module, called the Objecter, bridges the incoming stream of input from the image analysis module to the contents of the mental model (for other approaches to perceptually coupled simulation, see [37]- [39]). When an image region is found to stably exist for a sustained period of time, an object is instantiated by the Objecter in the mental model.…”

Section: Coupling Active Vision To the Mental Modelmentioning

confidence: 99%

Mental Imagery for a Conversational Robot

Roy

Hsiao

Mavridis

2004

IEEE Trans. Syst., Man, Cybern. B

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Abstract-To build robots that engage in fluid face-to-face spoken conversations with people, robots must have ways to connect what they say to what they see. A critical aspect of how language connects to vision is that language encodes points of view. The meaning of my left and your left differs due to an implied shift of visual perspective. The connection of language to vision also relies on object permanence. We can talk about things that are not in view. For a robot to participate in situated spoken dialog, it must have the capacity to imagine shifts of perspective, and it must maintain object permanence. We present a set of representations and procedures that enable a robotic manipulator to maintain a "mental model" of its physical environment by coupling active vision to physical simulation. Within this model, "imagined" views can be generated from arbitrary perspectives, providing the basis for situated language comprehension and production. An initial application of mental imagery for spatial language understanding for an interactive robot is described.Index Terms-Active vision, grounding, language, mental imagery, mental models, mental simulation, robots. I. SITUATED LANGUAGE USE IN USING language to convey meaning to listeners, speakers leverage situational context [1], [2]. Context may include many levels of knowledge ranging from the details of shared physical environments to cultural norms. As the degree of shared context decreases between communication partners, the efficiency of language also decreases since the speaker is forced to explicate increasing quantities of information that could otherwise be left unsaid. A sufficient lack of common ground can lead to communication failures.If machines are to engage in meaningful, fluent, situated spoken dialog, they must be aware of their situational context. As a starting point, we focus our attention on physical context. A machine that is aware of where it is, what it is doing, the presence and activities of other objects and people in its vicinity, and salient aspects of recent history, can use these contextual factors to interpret natural language.In numerous applications of spoken language technologies such as talking car navigation systems and speech-based control of portable devices, we envision machines that connect word meanings to the machine's immediate environments. For example, if a car navigation system could see landmarks in its vicinity based on computer vision, and anchor descriptive language to this visual perception, then the system would have a basis for generating contextually appropriate directions such as "Take a left turn immediately after the large red building." Con- sider also an assistive service robot that can lend a helping hand based on spoken requests from a human user. For the robot to properly interpret requests such as "Hand me the red cup and put it to the right of my plate," the robot must connect the meaning of verbs, nouns, adjectives, and spatial language to the robot's perceptual and action systems in a situationa...

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“…Surdu and Pooch [11] describe an agent-based simulation approach to real-time military planning. In their framework of "operationally-focused" simulations (OpSim) they define Operations Monitors (agents) whose function is to continually compare the internal simulation models with the real world operations.…”

Section: Related Effortsmentioning

confidence: 99%

A Simulation-optimization Approach to Air Warfare Planning

Popken

Cox

2004

Journal of Defense Modeling & Simulation

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How can computer-aided planning systems deal with the complexities, uncertainties, and rapidly shifting information needed to support air warfare operational planning? This paper uses a hierarchical decomposition of decision-making, coupled to a predictive simulation model that estimates the probability distribution of the outcomes of candidate operational plans. The approach will generate, evaluate, and improve Blue plans while assuming that Red intelligently reallocates its forces, using stochastic optimization, to counter Blue's moves. Evaluation of each Blue plan is accomplished via a Stochastic Evaluator that draws multiple samples of potential outcomes and Red force levels for a given Blue force structure and combined target composition. The evaluation metric is the net discounted value from enemy targets hit. Linear programming heuristics and simulation generate Red's adaptively optimized responses, outcomes, and inferred relative marginal force values. The results of this two-player, multi-level simulation-optimization approach for operational planning and decision-making demonstrate that automated plan optimization and embedding of optimization algorithms into an operational planning cycle operating over a multi-period conflict can be made practical for current computers by hierarchical decomposition of planning and on-line decision and optimization problems into computationally practical tasks.

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A methodology for applying simulation technologies in the mission operational environment

Cited by 5 publications

References 5 publications

C2 decision support system based on Symbiotic Simulation

C2 decision support system based on Symbiotic Simulation

Mental Imagery for a Conversational Robot

A Simulation-optimization Approach to Air Warfare Planning

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