Reasoning about Belief Based on Common Knowledge of Observability of Actions

Hideki Isozaki

Intelligent systems should work without bothering users. If they can guess what you think without asking you, they should do so. We, human beings, notice other people’s thoughts without direct communication. One’s thoughts depend on one’s belief. However, reasoning about belief is very difficult because various factors affect belief and they often lead to inconsistency. This paper presents a simple algorithm to calculate multiagent nested belief from an action sequence. The following three factors are essential in this algorithm: 1) the observability conditions of fluents and actions, 2) the direct/indirect effects of each action, and 3) the incompatibility of fluents. The algorithm performs regressive reasoning from a query. It has been tested by dozens of examples through a graphic interface. Experiments show the system gives plausible answers to various queries. This method will be useful in the construction of plan recognition systems and other advanced systems.


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