permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. With the expansion of distributed multiagent systems, traditional coordination strategy becomes a severe bottleneck when the system scales up to hundreds of agents. The key challenge is that in typical large multiagent systems, sparsely distributed agents can only communicate directly with very few others and the network is typically modeled as an adaptive complex network. In this paper, we present simulation testbed CoordSim built to model the coordination of network centric multiagent systems. Based on the token-based strategy, the coordination can be built as a communication decision problem that agents make decisions to ...
This paper considers the capability of collaboration and interaction between agents in a new archite...
Applications of deep reinforcement learning in multi-agent systems are a rapidly developing scientif...
Complex networks are an important methodology to model several (if not all) aspects of the real worl...
Large-scale multiagent teamwork has been popular in various domains. Similar to human society infras...
To form a cooperative multiagent team, autonomous agents are required to harmonize activities and ma...
One of the most significant problems in organizational scholarship is to discern how social collecti...
this paper, we address the limitations of existing models as they apply to very large agent teams. W...
In this paper we describe a dynamic, adaptive communication strategy for multiagent systems. We disc...
Efficient coordination among large numbers of heterogeneous agents promises to revolutionize the way...
Abstract—This paper presents a multi-agent model for large crowd simulations that addresses the need...
Coordination is a recurring theme in multiagent systems design. We consider the problem of achieving...
Building efficient distributed coordination algorithms is critical for the large scale multiagent sy...
Previous studies of team formation in multi-agent systems have typically assumed that the agent soci...
Coordination is a recurring theme in multiagent systems design. We consider the problem of achieving...
Whether in groups of humans or groups of computer agents, collaboration is most effective between in...
This paper considers the capability of collaboration and interaction between agents in a new archite...
Applications of deep reinforcement learning in multi-agent systems are a rapidly developing scientif...
Complex networks are an important methodology to model several (if not all) aspects of the real worl...
Large-scale multiagent teamwork has been popular in various domains. Similar to human society infras...
To form a cooperative multiagent team, autonomous agents are required to harmonize activities and ma...
One of the most significant problems in organizational scholarship is to discern how social collecti...
this paper, we address the limitations of existing models as they apply to very large agent teams. W...
In this paper we describe a dynamic, adaptive communication strategy for multiagent systems. We disc...
Efficient coordination among large numbers of heterogeneous agents promises to revolutionize the way...
Abstract—This paper presents a multi-agent model for large crowd simulations that addresses the need...
Coordination is a recurring theme in multiagent systems design. We consider the problem of achieving...
Building efficient distributed coordination algorithms is critical for the large scale multiagent sy...
Previous studies of team formation in multi-agent systems have typically assumed that the agent soci...
Coordination is a recurring theme in multiagent systems design. We consider the problem of achieving...
Whether in groups of humans or groups of computer agents, collaboration is most effective between in...
This paper considers the capability of collaboration and interaction between agents in a new archite...
Applications of deep reinforcement learning in multi-agent systems are a rapidly developing scientif...
Complex networks are an important methodology to model several (if not all) aspects of the real worl...