State estimation in multiagent settings involves updating an agent's belief over the physical states and the space of other agents' models. Performance of the previous approach to state estimation, the interactive particle filter, degrades with large ...
State estimation consists of updating an agent's belief given executed actions and observed evidence to date. In single agent environments, the state estimation can be formalized using the Bayes filter. Exact estimation can be performed in simple cases, ...
In order to act rationally, an agent must track the state of the environment over time. In the presence of other agents who themselves act, observe, and update their beliefs the agent must track not only the physical state but also the possible states ...
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