Command Decision Support Research Articles

Mining regular behaviors based on spatiotemporal trajectory multi‐dimensional features

In the military and civilian surveillance domain, it is of great significance to mine regular behaviours of targets for situation awareness and command decision support. Most of the existing trajectory clustering algorithms only consider the similarity of spatial position of the trajectory, without sufficient multi-dimensional information such as time, course and velocity. Some approaches based on information fusion take these multi-dimensional information into account, but the features with different dimensions fused by weight coefficients are not robust and universal for different scenarios. In this paper, a regular behaviour mining method based on spatiotemporal trajectory multi-dimensional features and density clustering is proposed. Firstly, multi-dimensional Hausdorff similarity is defined to measure spatiotemporal trajectory from different feature dimensionalities. Different from methods based on information fusion, the proposed method defines trajectory density in feature similarity of different dimensions and adaptively determines parameters according to feature distribution in different dimensions. Experimental results in simulated and radar measured trajectory data show that the proposed method can be accurate and robust in clustering evaluation indexes such as Purity, Precision, Recall and Rand Index from different scenarios, which has a good application prospect in intelligent surveillance tasks.

Conceptual Design of the Artificial Intelligence based Tactical Command Decision Support System using the Functional Analysis Method

Conceptual Design of the Artificial Intelligence based Tactical Command Decision Support System using the Functional Analysis Method

An Intelligent Knowledge Treasure for Military Decision Support

Information integration is great for military operations because the range of pertinent information sources is significantly distinct and dynamic. This article develops an intelligent knowledge treasure comprised of military resource ontology and procedures, as a learning model for better interoperability of heterogeneous resources of the Indian military. This model can interpret and learn the context of military information automatically, thereby facilitating the military commanders with decision making in several operations, such as command and control, teaching and training, military coalition, situation awareness and many more. To design the military resource ontology, this article specifies the core concepts of the ontology based on terms derived from heterogeneous resources. WWW standard ontology language, OWL has been used to codify the ontology. This article develops an intelligent tool—“QueryOnto”—as an interface to the military resource ontology that provides a commander decision support service and demonstrates how to apply the military ontology in practice. The developed ontology has been verified and validated with the best known approaches and metrics available. The presented model is helpful for military commanders to train their juniors in a systematic way and will provide an efficient web-based learning of different military tasks in future.

A Framework for Dynamic Context-Centric Commander Decision Support

This paper addresses the fundamental research question: “How can we determine the sequential decision- making process inside a decision maker’s mind?” We construct a dynamic Markov Decision Process using a Double Transition Model (DTM). The DTM is a cognitive model decomposing the decision-making process into episodic tasks that are extracted from a stream of incoming information. In a DTM, each state reflects a stage en route to a decision, and each action reflects a possible move from collecting data to hypothesizing and inferencing. The reward reflects how close a stage is to the final decision. We demonstrate this process through a proof-of-concept DTM using a hypothetical scenario for Typhoon Haiyan in the Philippines (2013). The DTM constructed from this scenario enables a Commander to reason about damaged areas, death tolls, and assistance methods while allowing his actions to be captured and used to explain why and how each decision is made.

Decision-making model to generate novel emergency response plans for improving coordination during large-scale emergencies

Developing joint emergency response plans is an effective method to coordinate multi-agency response endeavors. This study presents a novel emergency response plan structure that considers emergency command operation requirements, such as explicitly expressing the incident objective decomposition structure, formalizing decisions in a context-sensitive manner, supporting the synchronization of responding activities with variable interval, encoding complex temporal constraints, and providing temporal flexibility. A decision-making model is developed to generate these domain-specific action plans automatically based on integrating hierarchical task network (HTN) planning and scheduling technologies. This model presents several valuable contributions to existing state-based forwarding HTN planning paradigms. First, an enhanced HTN is designed to record traversed HTN exploration space for constructing of incident objective decomposition structure and decision-making contexts. Second, the model generates temporal flexible action plans that enable the handling of temporal uncertainty in the emergency response domain. A novel concurrency controlling mechanism to ensure the parallelism of response activities with variable intervals is also proposed based on the temporally enhanced planning state that represents a dynamic emergency situation. Finally, the proposed model explicitly represents the starting and ending time of all tasks in the task network to provide complete temporal flexibility. In particular, a dedicated temporal management method taking full advantage of the decomposition structure induced by the HTN planning process is proposed for propagating time constraints on the underling Simple Temporal Network (STN) incrementally. An empirical study on typhoon evacuation demonstrates that the presented model is suitable for solving real-world problems. Therefore, the decision-making model can be applied as a computational model for the development process of emergency response plans, and will be embedded as a reasoning logic in an emergency command decision support system.

Interactive computations: toward risk management in interactive intelligent systems.

Understanding the nature of interactions is regarded as one of the biggest challenges in projects related to complex adaptive systems. We discuss foundations for interactive computations in interactive intelligent systems (IIS), developed in the Wistech program and used for modeling complex systems. We emphasize the key role of risk management in problem solving by IIS. The considerations are based on experience gained in real-life projects concerning, e.g., medical diagnosis and therapy support, control of an unmanned helicopter, fraud detection algorithmic trading or fire commander decision support.

System Dynamics Model Simulation of Sea Battlefield Situation Assessment

The fundamental basis of Navy operational command decision support system is efficient to make an objective assessment of the complex dynamic sea battlefield situation. According to the study proposes the sea battlefield situation based on a system dynamics model evaluate simulation. First sea battlefield situation system analysis; second system causality analysis, to establish a causal loop diagram; again is based on the sea battlefield situation to assess the relationship between flow diagram, build SD simulation model; enter the initial parameter; finally, based on the events of the battlefield to enter the initial parameter, assessment simulation sea battlefield situation, analysis simulation conclusion, put forward suggestions.

Informing Design of a Command and Control Decision Support Interface through an Abstraction Hierarchy

The abstraction hierarchy can be used as a work domain analysis tool that provides a structured representation of a physical system under human supervisory control, and it aids in understanding complex human-machine interactions. The means-end relationships represented in the abstraction hierarchy provides a framework for highlighting areas that require knowledge-based reasoning through mapping processes and functions. These same abstract mappings can provide tangible insight into interface design relationships. We provide an example of using the abstraction hierarchy for this purpose in the development of a decision support tool for a military command and control interface. Allowing the abstraction hierarchy to inform interface design provides both an abstract and physical representation of system functional properties, which is especially critical in conceptualizing and designing an interface for a complex, time-pressured command and control domain.