Academia.eduAcademia.edu

Figure 1 – uploaded by Arwin Sumari

See full PDFdownloadDownload figure
Fig. 1 A simplified scenario of NCW paradigm thousands of locations [11]. A simplified scenario of the NCW paradigm is depicted in Fig. 1. So, in order that the obtained information can be used by the commandant to make a quick and correct decision, a system that is able to give comprehensive situational awareness information is extremely needed. Comprehensive information can be achieved by combining or fusing information that comes from diverse information sources.

Figure 1 A simplified scenario of NCW paradigm thousands of locations [11]. A simplified scenario of the NCW paradigm is depicted in Fig. 1. So, in order that the obtained information can be used by the commandant to make a quick and correct decision, a system that is able to give comprehensive situational awareness information is extremely needed. Comprehensive information can be achieved by combining or fusing information that comes from diverse information sources.

Related Figures (9)

Fig. 2 Human information fusion system [2]. The Information fusion mechanism emulates or mimics the human grandeur in making inference after observing the phenomenon in his/her environment by making use of his/her sensing organs. The sensing organs act as distributed sensors and the human brain acts as the information fusion system that fuses information obtained from the sensors. The result of fusion is an inference that will be used as a basis for decision making or doing an action. Information fusion is a part of cognitive process in the human brain. The human information fusion system is depicted in Fig. 2.
Fig. 2 Human information fusion system [2]. The Information fusion mechanism emulates or mimics the human grandeur in making inference after observing the phenomenon in his/her environment by making use of his/her sensing organs. The sensing organs act as distributed sensors and the human brain acts as the information fusion system that fuses information obtained from the sensors. The result of fusion is an inference that will be used as a basis for decision making or doing an action. Information fusion is a part of cognitive process in the human brain. The human information fusion system is depicted in Fig. 2.
3) Output: For the type of outputs, Dasarathy in [7], [10] has already defined them in detail. Fig. 5 presents the extension of Dasarathy process model level 0-2 that categorizes type of inputs and outputs.
3) Output: For the type of outputs, Dasarathy in [7], [10] has already defined them in detail. Fig. 5 presents the extension of Dasarathy process model level 0-2 that categorizes type of inputs and outputs.
Methods that are used for fusion mechanism is depended on the selected architecture and type of inputs will be fed to the IFS. [1], [8] summarizes the methods as follow:
Methods that are used for fusion mechanism is depended on the selected architecture and type of inputs will be fed to the IFS. [1], [8] summarizes the methods as follow:
Fig. 5 Extension of Dasarathy process model level 0-2 [7], [10] The concept of agent was introduced along with the growing of technology and the needs of computers/systems that are able to do the work intelligently. Recalling the complexity of the NCW paradigm, distributed sensors can be treated as intelligent agents that collect information and send the collected information to the main agent.
Fig. 5 Extension of Dasarathy process model level 0-2 [7], [10] The concept of agent was introduced along with the growing of technology and the needs of computers/systems that are able to do the work intelligently. Recalling the complexity of the NCW paradigm, distributed sensors can be treated as intelligent agents that collect information and send the collected information to the main agent.
For distributed sensors network, an individual agent has to work together with other individual agents to achieve common goals. This network of individual agents forms a multiagent system. A multiagent system is defined as a system that consists of a number of agents which interact with one another typically by exchanging messages through some computer network infrastructure [12]. Abstraction of relation of a multiagent system with its environment is depicted in Fig. 6.
For distributed sensors network, an individual agent has to work together with other individual agents to achieve common goals. This network of individual agents forms a multiagent system. A multiagent system is defined as a system that consists of a number of agents which interact with one another typically by exchanging messages through some computer network infrastructure [12]. Abstraction of relation of a multiagent system with its environment is depicted in Fig. 6.
INPUTS-OUTPUTS RELATION FOR MAIFS Inference Input (IEI) and Inference Output (IEO) are the extension of Dasarathy model. This input-output relation has been used when modelling MAIFS in [1]. Table I can be explained as follow:
INPUTS-OUTPUTS RELATION FOR MAIFS Inference Input (IEI) and Inference Output (IEO) are the extension of Dasarathy model. This input-output relation has been used when modelling MAIFS in [1]. Table I can be explained as follow:
The NCW architecture in Fig. 1 that will be modelled is just a simple illustration of the more complex one but it can be a stepping-stone for future promising works. For this example scenario, we divide the operation area into three areas. Area 1 is considered as headquarter as well as Departing Point (DP) for armed forces components, Area 2 as Trip Route (TR), and Area 3 as Battlefield (BD) where forces has to do its job. Fig. 7 presents the conversion from NCW architecture to a multiagent NCW system architecture.
The NCW architecture in Fig. 1 that will be modelled is just a simple illustration of the more complex one but it can be a stepping-stone for future promising works. For this example scenario, we divide the operation area into three areas. Area 1 is considered as headquarter as well as Departing Point (DP) for armed forces components, Area 2 as Trip Route (TR), and Area 3 as Battlefield (BD) where forces has to do its job. Fig. 7 presents the conversion from NCW architecture to a multiagent NCW system architecture.
There is no the most appropriate information method that can emulate the human IFS mechanism. In some cases, humar tends to perform probabilistic reasoning when assessing the phenomenon in his/her environment that sometimes uncertain. In effort to create agents that can emulate this mechanism, we need a method that deals with probabilistic reasoning namely probability theory. By employing probability theory, the agents’ knowledge can be represented by a measurement that we call as Degree of Certainty (DoC). [13] calls it as Degree of Belief (DoB) in the relevant sentences. Sentences in this case are entities states. One technique that is based on probability theory is Bayes
There is no the most appropriate information method that can emulate the human IFS mechanism. In some cases, humar tends to perform probabilistic reasoning when assessing the phenomenon in his/her environment that sometimes uncertain. In effort to create agents that can emulate this mechanism, we need a method that deals with probabilistic reasoning namely probability theory. By employing probability theory, the agents’ knowledge can be represented by a measurement that we call as Degree of Certainty (DoC). [13] calls it as Degree of Belief (DoB) in the relevant sentences. Sentences in this case are entities states. One technique that is based on probability theory is Bayes
Related topics:
Artificial IntelligenceMultiagent SystemsInformation FusionNetwork Centric WarfareDistributed Sensors
580 California St., Suite 400
San Francisco, CA, 94104
© 2025 Academia. All rights reserved