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Representing actions with an assumption-based truth maintenance system

Paul Morris, +1 more
- pp 13-17
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TLDR
An approach to applying the Assumption-based Truth Maintenance System to the task of representing the effects of actions, which extends traditional tree-structured context mechanisms to allow context merges and takes advantage of the underlying ATMS to detect inconsistent contexts and to maintain derived results.
Abstract
The Assumption-based Truth Maintenance System, introduced by de Kleer, is a powerful new tool for organizing a search through a space of alternatives. However, the ATMS is oriented towards inferential problem solving, and provides no special mechanisms for modeling actions or state changes. We describe an approach to applying the ATMS to the task of representing the effects of actions. The approach extends traditional tree-structured context mechanisms to allow context merges. It also takes advantage of the underlying ATMS to detect inconsistent contexts and to maintain derived results. Some results are presented concerning possible approaches to the treatment of merges in questionable circumstances. Finally, the analysis of actions in terms of a truth maintenance system suggests the need for a more elaborate treatment of contradiction in such systems than exists at present.

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A Model for Belief Revision.

TL;DR: In this article, the authors present a logic suitable for supporting belief revision systems, discuss the properties that a belief revision system based on this logic will exhibit, and present a particular implementation of their model of a belief-revision system, which differs from most of the systems developed so far in three respects: first, it is based on a logic that was developed to support belief revision, and it uses the rules of inference of the logic to automatically compute the dependencies among propositions rather than having to force the user to do this, as in many existing systems.
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A model for belief revision

TL;DR: This paper presents a logic suitable for supporting belief revision systems, discusses the properties that a belief revision system based on this logic will exhibit, and presents a particular implementation of the model of a belief revisions system.
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The qualitative process engine

TL;DR: Several general abstractions for organizing ATMS-based problem-solvers which are especially useful for envisioning are identified, including the many-worlds database, which avoids complex temporal reference schemes; how to organize problem-solving into justify/assume/interpret cycles which successively construct and extend partial solutions; and closed-world tables, which provide a mechanism for making closed- world assumptions.
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Reasoning with worlds and truth maintenance in a knowledge-based programming environment

TL;DR: The KEE system has been extended to include both a context (worlds) system and a truth maintenance system that combines a knowledge-based system development environment with a truth management system.
References
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Book

Principles of Artificial Intelligence

TL;DR: This classic introduction to artificial intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval.
Journal ArticleDOI

A truth maintenance system

TL;DR: The need of problem solvers to choose between alternative systems of beliefs is stressed, and a mechanism by which a problem solver can employ rules guiding choices of what to believe, what to want, and what to do is outlined.
Journal ArticleDOI

An assumption-based TMS

TL;DR: A new view of problem solving motivated by a new kind of truth maintenance system based on manipulating assumption sets is presented, which is possible to work effectively and efficiently with inconsistent information, context switching is free, and most backtracking is avoided.
Book

A Structure for Plans and Behavior

TL;DR: Progress to date in the ability of a computer system to understand and reason about actions is described, and the structure of a plan of actions is as important for problem solving and execution monitoring as the nature of the actions themselves.
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