Detecting intelligent agent behavior with environment abstraction in complex air combat systems
Detecting intelligent agent behavior with environment abstraction in complex air combat systems
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DOI：
10.1109/syscon.2013.6549953
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发表时间：
2013-04
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影响因子：
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通讯作者：
S. Mittal;Margery J. Doyle;Eric Watz
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文献类型：
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作者：
S. Mittal;Margery J. Doyle;Eric Watz
智能可以被定义为某些类型的复杂系统中的一种涌现属性，并且可能是由于代理与环境或通过环境变化直接或间接与其他代理交互的结果。从这个角度来看，智能采取了一种“观察者”现象的形式;外部观察的水平高于位于其环境中的代理人。这种涌现的行为有时可以被简化为系统内的基本组件及其相互作用的代理人，有时它是一个全新的行为，涉及一个新的命名。当紧急行为可以简化为它的部分时，它被认为是一种“弱”的紧急形式，当紧急行为不能简化为它的组成部分时，它被认为是一种“强”的紧急形式。这两种形式的涌现现象之间的一个区别因素是代理人对涌现结果的使用。在弱涌现中，没有因果关系，而在强涌现中，因果关系是基于涌现现象支持的可供性的行动的结果。建模一个复杂的空战系统涉及到建模代理行为在动态环境中，因为人类往往表现出强烈的涌现，观察涌现现象存在的知识边界内的领域的利益，以便不保证任何新的命名为计算模型在语义水平。所观察到的涌现现象必须在语义上被标记为“智能”，并且这种知识存在于语义域的范围内。因此，紧急智能行为的观察和识别已经通过环境抽象（EA）层的开发和使用进行，该环境抽象层在语义上确保可以在代理平台系统内对强涌现进行建模，例如分布式使命操作（DMO）测试平台中的实时、虚拟和建设性（LVC）训练。在本研究中，各种建模架构能够建模/模仿人类类型的行为或引发预期的反应，从人类飞行员在训练环境中的语义互操作性级别使用EA层承担。本文提出了一个高层次的描述代理平台系统和正式的建模和仿真方法，如离散事件系统（DEVS）的形式主义，可以用于建模复杂的动态系统捕捉紧急行为在各个层次的互操作性。本文提出的思想成功地实现了集成在语法层面上使用的分布交互仿真（DIS）协议的数据单元和语义互操作性与EA层。
Intelligence can be defined as an emergent property in some types of complex systems and may arise as a result of an agent's interactions with the environment or with other agents either directly or indirectly through changes in the environment. Within this perspective, intelligence takes the form of an `observer' phenomenon; externally observed at a level higher than that of agents situated in their environment. Such emergent behavior sometimes may be reduced to the fundamental components within the system and its interacting agents and sometimes it is a completely novel behavior involving a new nomenclature. When emergent behavior is reducible to its parts it is considered to be a `weak' form of emergence and when emergent behavior cannot be reduced to its constituent parts, it is considered to be a `strong' form of emergence. A differentiating factor between these two forms of emergent phenomena is the usage of emergent outcomes by the agents. In weak emergence there is no causality, while in strong emergence there is causation as a result of actions based on the affordances emergent phenomena support. Modeling a complex air combat system involves modeling agent behavior in a dynamic environment and because humans tend to display strong emergence, the observation of emergent phenomena has to exist within the knowledge boundaries of the domain of interest so as not to warrant any new nomenclature for the computational model at the semantic level. The emergent observed phenomenon has to be semantically tagged as `intelligent' and such knowledge resides within the bounds of the semantic domain. Therefore, observation and recognition of emergent intelligent behavior has been undertaken by the development and use of an Environment Abstraction (EA) layer that semantically ensures that strong emergence can be modeled within an agent-platform-system, such as Live, Virtual and Constructive (LVC) training in a Distributed Mission Operations (DMO) testbed. In the present study, various modeling architectures capable of modeling/mimicking human type behavior or eliciting an expected response from a human pilot in a training environment are brought to bear at the semantic interoperability level using the EA layer. This article presents a high level description of the agent-platform-system and how formal modeling and simulation approaches such as Discrete Event Systems (DEVS) formalism can be used for modeling complex dynamical systems capturing emergent behavior at various levels of interoperability. The ideas presented in this paper successfully achieve integration at the syntactic level using the Distributed Interactive Simulation (DIS) protocol data units and semantic interoperability with the EA layer.