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Multiple agent systems theory will be reviewed giving methods to supervise it.
This paper concerns the leader-follower multiple agent formation with nonlinear and coupled individual dynamics.
Agent-based thinking included difficulties in understanding energy states of agents and difficulties in understanding that aggregate outcomes may depend on multiple agent procedures.
These features are essential in multi-robot and human-robot contexts, where tasks need to be easily passed between systems and plan adaptation helps coping with the unpredictability inherent to systems where multiple agent make decisions.
In this article, we explore a general framework for assigning responsibility in multiple agent contexts.
This article has explored the structural model account of causal responsibility, with particular focus on simple multiple agent games.
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Since then, multiple agents and officers have been accused of wrongdoing.
Utilizing the information interaction and coordination among the neighboring networks based on multi-agent theory, we design novel and multiple agent-based robust fault detection filters (RFDFs) subject to only partial estimated and measured information.
We address the problem of optimal pathfinding for multiple agents.
The whole simulation system composed of multiple agents.
There are two problems in the process of learning optimal cooperative pursuit strategy for multiple agents.
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