Yonglin Lei

Domain-specific decision modelling and statistical analysis for combat system effectiveness simulation

Combat system effectiveness simulation (CoSES) needs to model both the physical aspect (i.e. physics modelling) and intelligent aspect (i.e. decision modelling) of combat systems. Combat platform decision-making has several characteristics such as cognition, diversity, agility, uncertainty and higher abstraction level, which bring tough challenges for decision model design, implementation and optimization. In this paper, we propose a domain-specific modelling approach which develops friendly modelling environments for model design, we design code generation mechanisms to transform domain-specific decision models to Python code which is supported by a Python script framework to implement decision models and we present a Bayesian network-based statistical analysis method on simulation output data to optimize the decision model. The case study shows that the proposed modelling and optimization approach effectively supports CoSES with decision models of higher efficiency and increased effectiveness.

A multi-paradigm decision modeling framework for combat system effectiveness measurement based on domain-specific modeling

Decision modeling is an essential part of the combat system effectiveness simulation (CoSES), which needs to cope with the cognitive quality, diversity, flexibility, and higher abstraction of decision making. In this paper, a multi-paradigm decision modeling framework is proposed to support decision modeling at three levels of abstraction based on domain-specific modeling (DSM). This framework designs a domain-specific modeling language (DSML) for decision modeling to raise the abstraction level of modeling, transforms the domain-specific models to formalism-based models to enable formal analysis and early verification and validation, and implements the semantics of the DSML based on a Python scripts framework which incorporates the decision model into the whole simulation system. The case study shows that the proposed approach incorporates domain expertise and facilitates domain modeler’s participation in CoSES to formulate the problem using DSML in the problem domain, and enables formal analysis and automatic implementation of the decision model in the solution domain.

A model framework-based domain-specific composable modeling method for combat system effectiveness simulation

Combat system effectiveness simulation (CoSES) plays an irreplaceable role in the effectiveness measurement of combat systems. According to decades of research and practice, composable modeling and multi-domain modeling are recognized as two major modeling requirements in CoSES. Current effectiveness simulation researches attempt to cope with the structural and behavioral complexity of CoSES based on a unified technological space, and they are limited to their existing modeling paradigms and fail to meet these two requirements. In this work, we propose a model framework-based domain-specific composable modeling method to solve this problem. This method builds a common model framework using application invariant knowledge for CoSES, and designs domain-specific modeling infrastructures for subdomains as corresponding extension points of the framework to support the modeling of application variant knowledge. Therefore, this method supports domain-specific modeling in multiple subdomains and the composition of subsystem models across different subdomains based on the model framework. The case study shows that this method raises the modeling abstraction level, supports generative modeling, and promotes model reuse and composability.

Behavioral DEVS metamodeling

A variety of metamodeling concepts, methods, and tools are available to todays modeling and simulation community. The Model Driven Architecture (MDA) framework enables modelers to develop platform independent models which can be transformed to platform-specific models. Considering model development according to the MDA framework, structural metamodeling is simpler as compared to behavioral metamodeling. In this paper, we shed light on and introduce behavioral metamodeling for atomic DEVS model. Behavior specification for an atomic DEVS model is examined from the standpoint of the MDA framework. A three-layer model abstraction consisting of metamodel, concrete model, and instance model is described from the vantage point of the DEVS formalism and the Eclipse Modeling Framework (EMF), a realization of MDA. A behavioral metamodel for atomic DEVS model is developed in EMF Ecore. This metamodel is introduced to complement the EMF-DEVS structural metamodeling. Some observations are discussed regarding behavioral metamodeling, model validation, and code generation.

A DSM-based multi-paradigm simulation modeling approach for complex systems

Complex systems contain hierarchical heterogeneous subsystems and diverse domain behavior patterns, which bring a grand challenge for simulation modeling. To cope with this challenge, the M&S community extends their existing modeling paradigms to promote reusability, interoperability and composability of simulation models and systems; however, these efforts are relatively isolated and limited to their own technical space. In this paper, we propose a domain specific modeling (DSM)-based multi-paradigm modeling approach which utilizes model driven engineering techniques to integrate current M&S paradigms and promote formal and automated model development. This approach constructs a simulation model framework to architect the structure of the overall simulation system and combines multiple M&S formalisms to describe the diverse domain behaviors; moreover, it provides domain specific language and environment support for conceptual modeling based on the model framework and formalisms. An application example on combat system effectiveness simulation illustrates the applicability of the approach.

Transforming statecharts to SMP2 for simulation modelling of complex systems

Modelling and Simulation (M&S) is an important methodology in complex systems research. Complex simulation systems have been developed to study the dynamic behaviors and temporal interactions of complex systems to gain insights in many disciplines. SMP2 is a simulation model standard to promote model portability and reuse and has been successfully used in several applications of complex simulation systems development. However, SMP2 lacks of behavioral modelling capability. In this paper, we integrate Statecharts, a pervasive behavioral modelling formalism, into SMP2-based M&S framework to empower SMP2 for complex simulation system development. We discuss SMP2 metamodel and Statecharts metamodel, design the mapping rules of the metamodels, and implement a prototype tool to transform Statecharts models to SMP2.

An Index Based Threat Modeling Method for Path Planning

Path planning is an effective means to improve the operational effectiveness of aircrafts. A reasonable estimation and description of threats existing in operation space are significant before generating a specific path for an aircraft. To avoid depending on experts’ experience excessively when we evaluate the threat situations, an Index Based Threat Modeling Method named IBTMM is proposed. IBTMM uses effectiveness indexes of defense systems to measure the threat of the aircraft faces and gives the dynamic threat degree which is changing according to the aircraft’s flying time and location. IBTMM does not give an absolute threat degree but a relative estimation of threats. When an aircraft is flying over a certain area, IBTMM can tell whether it is more dangerous or less than flying over other areas. IBTMM is helpful with the absence of simulation data in the earlier stage of path planning, as it reduces the planning space and meanwhile provides a good way to establish the path planning cost function. An example is presented to show the threat situation generated by IBTMM and demonstrate its effectiveness.

A Unifying Framework for UML Profile-based Cognitive Modeling: Development and Experience

To achieve model reuse, cognitive decision behaviors are usually implemented using a scripting language which is separate from the programming language used to implement simulation models. Therefore, it is desirable to establish a much better grounding for cognitive modeling. In the context of Domain-Specific Modeling (DSM), metamodeling from scratch for designing such a scripting language poses some limitations, among which is the issue of integrating various models that are represented by different customized languages, together with a large expenditure of designing, implementing, and maintaining these languages and their supporting resources. Instead, UML Profile-based metamodeling is adopted in this research, as a light weighted extension to capture the cognitive domain concepts, relationships, and constraints. Moreover, we propose a unifying framework for designing the domain specific profile where the expressiveness of cognitive domain specification is increased and the development cost and time decreased. Also, we present the development process by constructing a profile of Anti-Submarine Tactics (AST) and illustrate it by demonstrating an example with a scenario of armed escort.

The Route Planning Algorithm Based on Polygon Fusion

Route planning is widely used in public transportation, military and other fields. However, the mainstream algorithm adaptability is not comprehensive for the terrain, especially in barrier dense areas, such as A* algorithm, ant colony algorithm and so on. In these algorithms, time-consuming may be too high and planned route may be not optimal. To solve this problem, we propose a novel route planning algorithm based on polygon fusion (RABP). The basic principle of RABP is based on the plane geometry of the shortest line between two points, so the algorithm has strong guidance. Therefore, the algorithm has the advantages of low time-consuming and short route length. At the same time, because of the complex polygon fusion, too strong guidance would not make route planning cannot be accomplished. The algorithm needs to merge the barriers to avoid them and carry on route planning. Meanwhile, it will use the simplified operator to remove the redundant points on the planning route, so the final route is smoother and the route length is shorter. The experiment result shows that the RABP algorithm is more adaptive than A* algorithm and ant colony algorithm to dense barrier areas, the planning route is shorted and consumes less time.

WESS: A Generic Combat Effectiveness Simulation System

Combat Systems Effectiveness Simulation (CESS) is an important supportive means to combat systems analysis and conceptual design. Traditional approaches in developing CESS systems fall into two general categories. One is to apply generic simulation formalisms and platforms to build simulation applications each specific to a set of concrete application requirements. The other is to focus on a certain combat system domain for which a dedicated simulation system is developed. When confronted with non-functional issues like model reusability, simulation composability, and system evolvability, both find their limitations. Based on years experiences in CESS field and best practices found in overseas CESS systems, the model architecture is believed to be the key to develop CESS systems. In this paper, a model architecture-based generic CESS system, named WESS, is introduced. The design rationale, software architecture, application processes, and key aspects of WESS are briefed. A typical case study is given to demonstrate the functionalities of WESS. Practical applications tell WESS is able to help modelers to achieve those aims important to CESS including reusability, composability, and evolvability.