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Establishing joint goals through observation

When interacting with intelligent agents, it is vital to understand something of their intentions. Agents' intentions provide context in spoken deluge, help to define their future plans (and thus actions), and reveal information about their beliefs. We propose a method by which agents' intentions are inferred by observing their actions. Explicit communication among agents is not permitted. The joint intentions framework specifies the behaviors and obligations of agents that share in a cooperative intention. Our work focuses on the creation of such joint intentions through observation and plan recognition. The plan recognition structure uses Bayes nets to reason from observations to actions, and hidden Markov models to reason from sequences of actions to intent.