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Representing Plausible Beliefs about States, Actions, and Processes.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Representing Plausible Beliefs about States, Actions, and Processes./
作者:	Klassen, Toryn Qwyllyn.
面頁冊數:	1 online resource (203 pages)
附註:	Source: Dissertations Abstracts International, Volume: 82-10, Section: B.
Contained By:	Dissertations Abstracts International82-10B.
標題:	Artificial intelligence. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28156398click for full text (PQDT)
ISBN:	9798597082455

Representing Plausible Beliefs about States, Actions, and Processes.
Klassen, Toryn Qwyllyn.

Representing Plausible Beliefs about States, Actions, and Processes. - 1 online resource (203 pages)

Source: Dissertations Abstracts International, Volume: 82-10, Section: B.

Thesis (Ph.D.)--University of Toronto (Canada), 2021.

Includes bibliographical references

This thesis deals with the topic of modelling an agent's beliefs about a dynamic world in a way that allows for changes in beliefs, including retracting of beliefs, based on the agent's observations. We work within the field of knowledge representation, and represent the beliefs of the agent using a logical theory. In particular, we are concerned with representing what initial conditions the agent considers (im)plausible, what effects the agent thinks actions (im)plausibly have, and what processes in the environment the agent thinks have (im)plausibly occurred or will occur.Our approach uses the situation calculus, a standard knowledge representation framework for modelling action and change. Furthermore, we build on an existing framework in the situation calculus for modelling changing beliefs, where beliefs are determined using a plausibility ordering on situations. This supports modelling changing beliefs, since when the most plausible options are refuted by observations, the agent can fall back to the next most plausible options. Our concern is with how to specify this plausibility ordering using a logical theory. We propose to define the ordering by counting certain properties of situations, indicated by distinguished predicates, which we call "abnormality" predicates. This is inspired by how minimization of abnormalities has been used in circumscription, an approach to default reasoning.We show how beliefs about plausible and implausible action effects can be represented by having the axioms describing effects refer to abnormalities. Furthermore, we extend the account of belief to allow for beliefs about ongoing exogenous processes, described by a program (written in ConGolog, a standard programming language for use with the situation calculus). We show how having these programs refer to abnormalities allows for representing plausible and implausible environment behavior. Finally, we present a formal definition of "knowing how" to achieve goals, in terms of belief, which allows for the agent to change its beliefs about what it knows how to do.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798597082455Subjects--Topical Terms:

516317
Artificial intelligence.
Subjects--Index Terms:

Belief revisionIndex Terms--Genre/Form:

542853
Electronic books.

Representing Plausible Beliefs about States, Actions, and Processes.
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520 $a This thesis deals with the topic of modelling an agent's beliefs about a dynamic world in a way that allows for changes in beliefs, including retracting of beliefs, based on the agent's observations. We work within the field of knowledge representation, and represent the beliefs of the agent using a logical theory. In particular, we are concerned with representing what initial conditions the agent considers (im)plausible, what effects the agent thinks actions (im)plausibly have, and what processes in the environment the agent thinks have (im)plausibly occurred or will occur.Our approach uses the situation calculus, a standard knowledge representation framework for modelling action and change. Furthermore, we build on an existing framework in the situation calculus for modelling changing beliefs, where beliefs are determined using a plausibility ordering on situations. This supports modelling changing beliefs, since when the most plausible options are refuted by observations, the agent can fall back to the next most plausible options. Our concern is with how to specify this plausibility ordering using a logical theory. We propose to define the ordering by counting certain properties of situations, indicated by distinguished predicates, which we call "abnormality" predicates. This is inspired by how minimization of abnormalities has been used in circumscription, an approach to default reasoning.We show how beliefs about plausible and implausible action effects can be represented by having the axioms describing effects refer to abnormalities. Furthermore, we extend the account of belief to allow for beliefs about ongoing exogenous processes, described by a program (written in ConGolog, a standard programming language for use with the situation calculus). We show how having these programs refer to abnormalities allows for representing plausible and implausible environment behavior. Finally, we present a formal definition of "knowing how" to achieve goals, in terms of belief, which allows for the agent to change its beliefs about what it knows how to do.
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653 $a Reasoning about action
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