The accomplishment of a complex problem usually involves cooperation between participators with different knowledge background concerned. This paper identifies interdependency between different sub problems （through ...The accomplishment of a complex problem usually involves cooperation between participators with different knowledge background concerned. This paper identifies interdependency between different sub problems （through problem decomposition） as the major factor that influences cooperative relations in multi-Agent systems, based on which we propose an efficient means to measure cooperation coefficient （degree） between different Agents. Then cognitive cooperation between Agents is analyzed which aims at collecting the wisdom of the cognitive community for a systematic solution to the overall problem.展开更多
In this paper, rough set theory is introduced into the interface multi-agent system （MAS） for industrial supervisory system. Taking advantages of rough set in data mining, a cooperation model for MAS is built. Rules...In this paper, rough set theory is introduced into the interface multi-agent system （MAS） for industrial supervisory system. Taking advantages of rough set in data mining, a cooperation model for MAS is built. Rules for avoiding cooperation conflict are deduced. An optimization algorithm is used to enhance security and real time attributes of the system. An application based on the proposed algorithm and rules are given.展开更多
Aiming at the problem on cooperative air-defense of surface warship formation, this paper maps the cooperative airdefense system of systems （SoS） for surface warship formation （CASoSSWF） to the biological immune s...Aiming at the problem on cooperative air-defense of surface warship formation, this paper maps the cooperative airdefense system of systems （SoS） for surface warship formation （CASoSSWF） to the biological immune system （BIS） according to the similarity of the defense mechanism and characteristics between the CASoSSWF and the BIS, and then designs the models of components and the architecture for a monitoring agent, a regulating agent, a killer agent, a pre-warning agent and a communicating agent by making use of the theories and methods of the artificial immune system, the multi-agent system （MAS）, the vaccine and the danger theory （DT）. Moreover a new immune multi-agent model using vaccine based on DT （IMMUVBDT） for the cooperative air-defense SoS is advanced. The immune response and immune mechanism of the CASoSSWF are analyzed. The model has a capability of memory, evolution, commendable dynamic environment adaptability and self-learning, and embodies adequately the cooperative air-defense mechanism for the CASoSSWF. Therefore it shows a novel idea for the CASoSSWF which can provide conception models for a surface warship formation operation simulation system.展开更多
A cooperative multi-robot system (CMRS) modeling method called fuzzy timed agent based Petri nets (FTAPN) is proposed in this paper, which has been extended from fuzzy timed object-oriented Petri net (FTOPN). The prop...A cooperative multi-robot system (CMRS) modeling method called fuzzy timed agent based Petri nets (FTAPN) is proposed in this paper, which has been extended from fuzzy timed object-oriented Petri net (FTOPN). The proposed FTAPN can be used to model and illustrate both the structural and dynamic aspects of CMRS, which is a typical multi-agent system (MAS). At the same time, supervised learning is supported in FTAPN. As a special type of high-level object, agent is introduced into FTAPN, which is used as a common modeling object in its model. The proposed FTAPN can not only be used to model CMRS and represent system aging effect, but also be refined into the object-oriented implementation easily. At the same time, it can also be regarded as a conceptual and practical artificial intelligence (AI) tool for multi-agent systems (MAS) into the mainstream practice of the software development.展开更多
Cooperative multi-agent reinforcement learning（ MARL） is an important topic in the field of artificial intelligence,in which distributed constraint optimization（ DCOP） algorithms have been widely used to coordinat...Cooperative multi-agent reinforcement learning（ MARL） is an important topic in the field of artificial intelligence,in which distributed constraint optimization（ DCOP） algorithms have been widely used to coordinate the actions of multiple agents. However,dense communication among agents affects the practicability of DCOP algorithms. In this paper,we propose a novel DCOP algorithm dealing with the previous DCOP algorithms＇ communication problem by reducing constraints.The contributions of this paper are primarily threefold：（1） It is proved that removing constraints can effectively reduce the communication burden of DCOP algorithms.（2） An criterion is provided to identify insignificant constraints whose elimination doesn＇t have a great impact on the performance of the whole system.（3） A constraint-reduced DCOP algorithm is proposed by adopting a variant of spectral clustering algorithm to detect and eliminate the insignificant constraints. Our algorithm reduces the communication burdern of the benchmark DCOP algorithm while keeping its overall performance unaffected. The performance of constraint-reduced DCOP algorithm is evaluated on four configurations of cooperative sensor networks. The effectiveness of communication reduction is also verified by comparisons between the constraint-reduced DCOP and the benchmark DCOP.展开更多
基金Supported by the National Natural Science Foun-dation of China (60303025 )and the Natural Science Foundation ofJiangsu Province for Youth Scholar (BK2004411)
文摘The accomplishment of a complex problem usually involves cooperation between participators with different knowledge background concerned. This paper identifies interdependency between different sub problems （through problem decomposition） as the major factor that influences cooperative relations in multi-Agent systems, based on which we propose an efficient means to measure cooperation coefficient （degree） between different Agents. Then cognitive cooperation between Agents is analyzed which aims at collecting the wisdom of the cognitive community for a systematic solution to the overall problem.
基金Project supported by Science Foundation of Shanghai MunicipalCommission of Science and Technology (Grant Nos .025111052 ,04JC14038)
文摘In this paper, rough set theory is introduced into the interface multi-agent system （MAS） for industrial supervisory system. Taking advantages of rough set in data mining, a cooperation model for MAS is built. Rules for avoiding cooperation conflict are deduced. An optimization algorithm is used to enhance security and real time attributes of the system. An application based on the proposed algorithm and rules are given.
文摘Aiming at the problem on cooperative air-defense of surface warship formation, this paper maps the cooperative airdefense system of systems （SoS） for surface warship formation （CASoSSWF） to the biological immune system （BIS） according to the similarity of the defense mechanism and characteristics between the CASoSSWF and the BIS, and then designs the models of components and the architecture for a monitoring agent, a regulating agent, a killer agent, a pre-warning agent and a communicating agent by making use of the theories and methods of the artificial immune system, the multi-agent system （MAS）, the vaccine and the danger theory （DT）. Moreover a new immune multi-agent model using vaccine based on DT （IMMUVBDT） for the cooperative air-defense SoS is advanced. The immune response and immune mechanism of the CASoSSWF are analyzed. The model has a capability of memory, evolution, commendable dynamic environment adaptability and self-learning, and embodies adequately the cooperative air-defense mechanism for the CASoSSWF. Therefore it shows a novel idea for the CASoSSWF which can provide conception models for a surface warship formation operation simulation system.
文摘A cooperative multi-robot system (CMRS) modeling method called fuzzy timed agent based Petri nets (FTAPN) is proposed in this paper, which has been extended from fuzzy timed object-oriented Petri net (FTOPN). The proposed FTAPN can be used to model and illustrate both the structural and dynamic aspects of CMRS, which is a typical multi-agent system (MAS). At the same time, supervised learning is supported in FTAPN. As a special type of high-level object, agent is introduced into FTAPN, which is used as a common modeling object in its model. The proposed FTAPN can not only be used to model CMRS and represent system aging effect, but also be refined into the object-oriented implementation easily. At the same time, it can also be regarded as a conceptual and practical artificial intelligence (AI) tool for multi-agent systems (MAS) into the mainstream practice of the software development.
基金Supported by the National Social Science Foundation of China(15ZDA034,14BZZ028)Beijing Social Science Foundation(16JDGLA036)JKF Program of People’s Public Security University of China(2016JKF01318)
文摘Cooperative multi-agent reinforcement learning（ MARL） is an important topic in the field of artificial intelligence,in which distributed constraint optimization（ DCOP） algorithms have been widely used to coordinate the actions of multiple agents. However,dense communication among agents affects the practicability of DCOP algorithms. In this paper,we propose a novel DCOP algorithm dealing with the previous DCOP algorithms＇ communication problem by reducing constraints.The contributions of this paper are primarily threefold：（1） It is proved that removing constraints can effectively reduce the communication burden of DCOP algorithms.（2） An criterion is provided to identify insignificant constraints whose elimination doesn＇t have a great impact on the performance of the whole system.（3） A constraint-reduced DCOP algorithm is proposed by adopting a variant of spectral clustering algorithm to detect and eliminate the insignificant constraints. Our algorithm reduces the communication burdern of the benchmark DCOP algorithm while keeping its overall performance unaffected. The performance of constraint-reduced DCOP algorithm is evaluated on four configurations of cooperative sensor networks. The effectiveness of communication reduction is also verified by comparisons between the constraint-reduced DCOP and the benchmark DCOP.
