The brain-inspired software architecture will be built as shown in Fig. 1c. Supported by
common operating systems such as Linux/Unix or Window Server, software modules
corresponding to various nodes are realized, such as general brain-inspired nodes,
brain-inspired learning nodes, brain-inspired memory nodes, and brain-inspired
knowledge nodes. By interconnection of brain-inspired nodes, the mechanisms and
functions of processes like learning and memory of super-brain network system are
achieved, supporting the command and control system for the brain-inspired cognitive
pattern, providing dynamic adaptive intelligent services for the fight.
From the above evolution path, we can see that the dynamic adaption based on
brain-inspired software architecture is the advanced stage of the invocation pattern of
intelligence algorithms in command and control systems. Based on brain-inspired
software architecture, combined with brain-inspired algorithms such as autonomous
reinforcement learning, the construction of super-brain network system can achieve
general intelligence ability for command and control system to some degree, in ways of
speech recognition, image analysis, knowledge reasoning, augmented reality, natural
language processing, etc. Moreover, it provides intelligent support for domains such as
situation awareness, command and decision, action control, support and guarantee, etc.,
thus achieving fast awareness of battlefield situation, scientific command and decisionmaking, agile control of actions as the occasion requires, and real-time guarantee of
material support, gaining the ability of SoS intelligence.
5 Conclusion
In this paper we analyze the development tendency of intelligentization in military
command and control system, which will be from specialized intelligence to general
intelligence, and from intelligence of point to intelligence of SoS. The advantages of
brain-inspired intelligence in learning with small samples, anti-noising, and general
intelligence, contribute to promoting general intelligence and SoS intelligence in
command and control system. Besides, the evolution path of invocation pattern of
intelligent algorithms in command and control system can be divided into three stages:
specialized invocation of specialized algorithms, invocation of general algorithms as
required and dynamic adaption based on brain-inspired software architectures.
References
1. U.S. DoD Defense Science Board, (2016) Summer study on autonomy. http://
autonomousweapons.org/department-of-defense-science-board-summer-study-on-autonmy/
2. Turing AM (1950) Computing machinery and intelligence. Mind 49:433–460
3. Wilson R, Keil F (1999) The MIT encyclopedia of the cognitive sciences. MIT, Cambridge,
MA
4. Maass W (1997) Networks of spiking neurons: the third generation of neural network
models. Neural Netw 10(9):1659–1671
5. Dayan P, Abbott LF (2003) Computational and mathematical modeling of neural systems:
Model neurons I: Neuroelectronic. MIT Press, Cambridge
Applications of Brain-Inspired Intelligence …
389
common operating systems such as Linux/Unix or Window Server, software modules
corresponding to various nodes are realized, such as general brain-inspired nodes,
brain-inspired learning nodes, brain-inspired memory nodes, and brain-inspired
knowledge nodes. By interconnection of brain-inspired nodes, the mechanisms and
functions of processes like learning and memory of super-brain network system are
achieved, supporting the command and control system for the brain-inspired cognitive
pattern, providing dynamic adaptive intelligent services for the fight.
From the above evolution path, we can see that the dynamic adaption based on
brain-inspired software architecture is the advanced stage of the invocation pattern of
intelligence algorithms in command and control systems. Based on brain-inspired
software architecture, combined with brain-inspired algorithms such as autonomous
reinforcement learning, the construction of super-brain network system can achieve
general intelligence ability for command and control system to some degree, in ways of
speech recognition, image analysis, knowledge reasoning, augmented reality, natural
language processing, etc. Moreover, it provides intelligent support for domains such as
situation awareness, command and decision, action control, support and guarantee, etc.,
thus achieving fast awareness of battlefield situation, scientific command and decisionmaking, agile control of actions as the occasion requires, and real-time guarantee of
material support, gaining the ability of SoS intelligence.
5 Conclusion
In this paper we analyze the development tendency of intelligentization in military
command and control system, which will be from specialized intelligence to general
intelligence, and from intelligence of point to intelligence of SoS. The advantages of
brain-inspired intelligence in learning with small samples, anti-noising, and general
intelligence, contribute to promoting general intelligence and SoS intelligence in
command and control system. Besides, the evolution path of invocation pattern of
intelligent algorithms in command and control system can be divided into three stages:
specialized invocation of specialized algorithms, invocation of general algorithms as
required and dynamic adaption based on brain-inspired software architectures.
References
1. U.S. DoD Defense Science Board, (2016) Summer study on autonomy. http://
autonomousweapons.org/department-of-defense-science-board-summer-study-on-autonmy/
2. Turing AM (1950) Computing machinery and intelligence. Mind 49:433–460
3. Wilson R, Keil F (1999) The MIT encyclopedia of the cognitive sciences. MIT, Cambridge,
MA
4. Maass W (1997) Networks of spiking neurons: the third generation of neural network
models. Neural Netw 10(9):1659–1671
5. Dayan P, Abbott LF (2003) Computational and mathematical modeling of neural systems:
Model neurons I: Neuroelectronic. MIT Press, Cambridge
Applications of Brain-Inspired Intelligence …
389