A method for reasoning about other agents' beliefs from observations
نویسنده
چکیده
This paper is concerned with the problem of how to make inferences about an agent’s beliefs based on an observation of how that agent responded to a sequence of revision inputs over time. We collect and review some earlier results for the case where the observation is complete in the sense that (i) the logical content of all formulae appearing in the observation is known, and (ii) all revision inputs received by the agent during the observed period are recorded in the observation. Then we provide new results for the more general case where information in the observation might be distorted due to noise or some revision inputs are missing altogether. Our results are based on the assumption that the agent employs a specific, but plausible, belief revision framework when incorporating new information.
منابع مشابه
A Decision-Theoretic Approach to Evaluating Posterior Probabilities of Mental Models
Agents face the problem of maintaining and updating their beliefs over the possible mental models (whether goals, plans, activities, intentions, etc.) of other agents in many multiagent domains. Decision-theoretic agents typically model their uncertainty in these beliefs as a probability distribution over their possible mental models of others. They then update their beliefs by computing a post...
متن کاملInformation-Based Agents Model other Agents by Observing their Actions
An ‘information-based’ agent is proposed for competitive multi-issue negotiation, where speculation about an opponent’s motivation necessarily leads to an endless counter-speculation spiral of questionable value. Information-based agents model other agents by observing their behaviour and not by making assumptions concerning their motivations or internal reasoning. The integrity of these agents...
متن کاملA Probabilistic Doxastic Temporal Logic for Reasoning about Beliefs in Multi-agent Systems
We present Probabilistic Doxastic Temporal (PDT) Logic, a formalism to represent and reason about probabilistic beliefs and their temporal evolution in multi-agent systems. This formalism builds upon recent work on APT Logic. It enables the quantification of beliefs through probability intervals and incorporates the concepts of frequency functions and epistemic actions. We show how agents can u...
متن کاملMultiple Agents and the Heuristic Ascription of Belief
A method for heuristically generating nested beliefs (what some agent believes that another agent-believes ... about a topic) is described. Such nested beliefs (points of view) are esential to many processes such as discourse processing and reasoning about other agents' reasoning processes. Particular interest is paid to the class of beliefs known as atypical beliefs and to intensional descript...
متن کاملReasoning about Incomplete Agents
We show how the subjective and nonmonotonic belief logic SL formalizes an agent’s reasoning about the beliefs of incomplete agents. SL provides the logical foundation of SIMBA, an implemented belief reasoning system which constitutes part of an artificial cognitive agent called Cassie. The emphasis of SIMBA is on belief ascription, i.e., on governing Cassie’s reasoning about the beliefs of othe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2007