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人工智能的自然之维 被引量:6
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作者 李珍 《云南社会科学》 CSSCI 北大核心 2020年第1期40-46,186,共8页
在人工智能问题研究中,向来缺乏对人工智能本质的本体论思考,而实际上,在智能问题上对"自然"与"人工"的概念做哲学上的反思,与人工智能研究的诸多问题有密切关联。"自然"与"人工"并无界限之分... 在人工智能问题研究中,向来缺乏对人工智能本质的本体论思考,而实际上,在智能问题上对"自然"与"人工"的概念做哲学上的反思,与人工智能研究的诸多问题有密切关联。"自然"与"人工"并无界限之分,只有程度之异,科学实验的可靠性论证及达尔文进化论中从人工选择到自然选择的推演都证实了这一点。自然智能与人工智能同样如此,智能不能被严格地划分为自然和人工,两者虽然在产生方式与实现载体上不同,但从进化的角度看,它们是自然界在不同阶段的产物。 展开更多
关键词 人工智能 自然 智能统一性
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Consensus control for multi-agents in a non-rectangular bounded space: algorithmand experiments
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作者 朱德政 田玉平 《Journal of Southeast University(English Edition)》 EI CAS 2015年第1期74-79,共6页
Aiming for the coordinated motion and cooperative control of multi-agents in a non-rectangular bounded space, a velocity consensus algorithm for the agents with double- integrator dynamics is presented. The traditiona... Aiming for the coordinated motion and cooperative control of multi-agents in a non-rectangular bounded space, a velocity consensus algorithm for the agents with double- integrator dynamics is presented. The traditional consensus algorithm for bounded space is only applicable to rectangular bouncing boundaries, not suitable for non-rectangular space. In order to extend the previous consensus algorithm to the non- rectangular space, the concept of mirrored velocity is introduced, which can convert the discontinuous real velocity to continuous mirrored velocity, and expand a bounded space into an infinite space. Using the consensus algorithm, it is found that the mirrored velocities of multi-agents asymptotically converge to the same values. Because each mirrored velocity points to a unique velocity in real space, it can be concluded that the real velocities of multi-agents also asymptotically converge. Finally, the effectiveness of the proposed consensus algorithm is examined by theoretical proof and numerical simulations. Moreover, an experiment is performed with the algorithm in a real multi-robot system successfully. 展开更多
关键词 multi-agent system CONSENSUS non-rectangularbounded space mirrored velocity
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Output Consensus for Heterogeneous Nonlinear Multi-Agent Systems Based on T-S Fuzzy Model 被引量:3
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作者 LI Xiaolei LUO Xiaoyuan +1 位作者 LI Shaobao GUAN Xinping 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2017年第5期1042-1060,共19页
In this paper, the output consensus problem of general heterogeneous nonlinear multi-agent systems subject to different disturbances is considered. A kind of Takagi-Sukeno fuzzy modeling method is used to describe the... In this paper, the output consensus problem of general heterogeneous nonlinear multi-agent systems subject to different disturbances is considered. A kind of Takagi-Sukeno fuzzy modeling method is used to describe the nonlinear agents' dynamics. Based on the model, a distributed fuzzy observer and controller are designed based on parallel distributed compensation scheme and internal reference models such that the heterogeneous nonlinear multi-agent systems can achieve output consensus. Then a necessary and sufficient condition is presented for the output consensus problem. And it is shown that the consensus trajectory of the global fuzzy model is determined by the network topology and the initial states of the internal reference models. Finally, some simulations are given to illustrate and verify the effectiveness of the proposed scheme. 展开更多
关键词 Heterogeneous nonlinear multi-agent system internal reference model output consensus T-S fuzzy model.
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CONSENSUS CONTROL DESIGN FOR MULTI-AGENT SYSTEMS USING RELATIVE OUTPUT FEEDBACK 被引量:1
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作者 WANG Jinhuan LIU Zhixin HU Xiaoming 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2014年第2期237-251,共15页
This paper studies the consensus problem of multi-agent systems in which all agents are modeled by a general linear system. The authors consider the case where only the relative output feedback between the neighboring... This paper studies the consensus problem of multi-agent systems in which all agents are modeled by a general linear system. The authors consider the case where only the relative output feedback between the neighboring agents can be measured. To solve the consensus problem, the authors first construct a static relative output feedback control under some mild constraints on the system model. Then the authors use an observer based approach to design a dynamic relative output feedback control. If the adjacent graph of the system is undirected and connected or directed with a spanning tree, with the proposed control laws, the consensus can be achieved. The authors note that with the observer based approach, some information exchange between the agents is needed unless the associated adjacent graph is completely connected. 展开更多
关键词 CONSENSUS decentralized control multi-agent systems observer.
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Finite-time adaptive consensus of a class of multi-agent systems 被引量:16
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作者 LIU KeXin WU LuLu +1 位作者 Lü JinHu ZHU HengHui 《Science China(Technological Sciences)》 SCIE EI CAS CSCD 2016年第1期22-32,共11页
Multi-agent systems(MASs) are ubiquitous in natural and artificial systems. This paper aims to establish the finite-time adaptive consensus criterion for a class of MASs with nonlinear dynamics. Traditionally, the fin... Multi-agent systems(MASs) are ubiquitous in natural and artificial systems. This paper aims to establish the finite-time adaptive consensus criterion for a class of MASs with nonlinear dynamics. Traditionally, the finite-time consensus criterion is often established based on the prior information on Lipschitz constants and the eigenvalues of Laplacian matrix. However, it is difficult to acquire the above prior information for most real-world engineering systems. To overcome the above difficulty, this paper develops the finite-time consensus criteria for a class of MASs with nonlinear dynamics via adaptive technique. In detail, we design the finite-time distributed node-based and edge-based adaptive consensus protocols for a class of MASs with fixed and switching topologies. Numerical simulations are also given to validate the proposed finite-time adaptive consensus criterion. 展开更多
关键词 Multi-agent systems adaptive control finite-time consensus switching topology
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