supported in part by National Key Research and Development Program of China(Grant No.2020AAA0107200);National Natural Science Foundation of China(Grant Nos.61876119,61921006);Natural Science Foundation of Jiangsu(GrantNo.BK20221442)。
Team adaptation to new cooperative tasks is a hallmark of human intelligence,which has yet to be fully realized in learning agents.Previous studies on multi-agent transfer learning have accommodated teams of different...
supported by National Natural Science Foundation of China(Grant No.62036002);Beijing Natural Science Foundation(Grant No.1244045)。
Evolutionary game theory(EGT)and artificial intelligence(AI)are two fields that,at first glance,might seem distinct,but they have notable connections and intersections.The former focuses on the evolution of behaviors(...
supported by National Natural Science Foundation of China(Grant Nos.62192731,62192730,62190200).
This paper proposes an imitation learning method to learn a universal agent policy for unlabeled multi-agent pathfinding(unlabeled MAPF)in grid environments.The method transforms the unlabeled MAPF problem into a seri...
supported in part by National Natural Science Foundation of China (Grant Nos.62371462,61931020,62101569,U19B2024);Natural Science Foundation of Hunan Province (Grant No.2022JJ10068);Science and Technology Innovation Program of Hunan Province (Grant No.2022RC1093)。
Unmanned aerial vehicles(UAVs)are recognized as effective means for delivering emergency communication services when terrestrial infrastructures are unavailable.This paper investigates a multiUAV-assisted communicatio...
supported by National Natural Science Foundation of China(Grant No.61773198)。
In cooperative multi-agent reinforcement learning(MARL),where agents only have access to partial observations,efficiently leveraging local information is critical.During long-time observations,agents can build awarene...
National Key R&D Program of China(Grant No.2018YFA0703800);National Natural Science Foundation of China(Grant Nos.61873262,61733018,61333001)。
Dear editor,Recent years have witnessed a rapid growth of distributed design in multi-agent networks because of the scalability,robustness and low cost.Compared with the conventional centralized and parallel design,al...
supported by National Natural Science Foundation of China (Grant Nos. 61573200, 61573199)
This work studies the leader-following consensus problem of second-order nonlinear multi-agent systems with aperiodically intermittent position measurements. Through the filter-based method, a novel intermittent conse...
supported by National Natural Science Foundation of China (Grant Nos. 61751301, 61533001, 61873074)
This paper investigates the state consensus for double-integrator networks under heterogeneous interaction topologies. For double-integrator networks, the setting of heterogeneous topologies means that position and ve...
supported by National Natural Science Foundation of China (Grant Nos. 61873011, 61803014, 61503009, 61333011);Beijing Natural Science Foundation (Grant No. 4182035);Young Elite Scientists Sponsorship Program by CAST (Grant No. 2017QNRC001);Aeronautical Science Foundation of China (Grant Nos. 2016ZA51005, 20170151001);Special Research Project of Chinese Civil Aircraft, State Key Laboratory of Intelligent Control and Decision of Complex Systems;Fundamental Research Funds for the Central Universities (Grant No. YWF-18-BJ-Y-73)
For maneuvering target tracking with sensor faults, consensus-based distributed state estimation problems are studied herein. The communication status of the nonlinear system composed of multiple agents is described u...
supported by National Natural Science Foundation of China (Grant Nos. 61375120, 61533001, 61374199)
In this paper, we investigate the controllability problem of multi-agent systems with switching topology over finite fields. The multi-agent system is defined over finite fields, where agents process only values from ...