Regression with respect to sensing actions and partial states

Le Chi Tuan; Chitta Baral; Xin Zhang; Tran Cao Son

Regression with respect to sensing actions and partial states

Le Chi Tuan, Chitta Baral, Xin Zhang, Tran Cao Son

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

In this paper, we present a state-based regression function for planning domains where an agent does not have complete information and may have sensing actions. We consider binary domains ', and employ the 0-approximation (Son & Baral 2001) to define the regression function. In binary domains, the use of 0-approximation means using 3-valued states. Although planning using this approach is incomplete with respect to the full semantics, we adopt it to have a lower complexity. We prove the soundness and completeness of our regression formulation with respect to the definition of progression and develop a conditional planner that utilizes our regression function.

Original language	English (US)
Title of host publication	Proceedings of the National Conference on Artificial Intelligence
Pages	556-561
Number of pages	6
State	Published - 2004
Event	Proceedings - Nineteenth National Conference on Artificial Intelligence (AAAI-2004): Sixteenth Innovative Applications of Artificial Intelligence Conference (IAAI-2004) - San Jose, CA, United States Duration: Jul 25 2004 → Jul 29 2004

Other

Other	Proceedings - Nineteenth National Conference on Artificial Intelligence (AAAI-2004): Sixteenth Innovative Applications of Artificial Intelligence Conference (IAAI-2004)
Country/Territory	United States
City	San Jose, CA
Period	7/25/04 → 7/29/04

ASJC Scopus subject areas

Software

Cite this

Tuan, LC, Baral, C, Zhang, X & Son, TC 2004, Regression with respect to sensing actions and partial states. in Proceedings of the National Conference on Artificial Intelligence. pp. 556-561, Proceedings - Nineteenth National Conference on Artificial Intelligence (AAAI-2004): Sixteenth Innovative Applications of Artificial Intelligence Conference (IAAI-2004), San Jose, CA, United States, 7/25/04.

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author = "Tuan, {Le Chi} and Chitta Baral and Xin Zhang and Son, {Tran Cao}",

year = "2004",

language = "English (US)",

pages = "556--561",

booktitle = "Proceedings of the National Conference on Artificial Intelligence",

note = "Proceedings - Nineteenth National Conference on Artificial Intelligence (AAAI-2004): Sixteenth Innovative Applications of Artificial Intelligence Conference (IAAI-2004) ; Conference date: 25-07-2004 Through 29-07-2004",

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AU - Tuan, Le Chi

AU - Baral, Chitta

AU - Zhang, Xin

AU - Son, Tran Cao

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AB - In this paper, we present a state-based regression function for planning domains where an agent does not have complete information and may have sensing actions. We consider binary domains ', and employ the 0-approximation (Son & Baral 2001) to define the regression function. In binary domains, the use of 0-approximation means using 3-valued states. Although planning using this approach is incomplete with respect to the full semantics, we adopt it to have a lower complexity. We prove the soundness and completeness of our regression formulation with respect to the definition of progression and develop a conditional planner that utilizes our regression function.

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M3 - Conference contribution

AN - SCOPUS:9444290409

SP - 556

EP - 561

BT - Proceedings of the National Conference on Artificial Intelligence

T2 - Proceedings - Nineteenth National Conference on Artificial Intelligence (AAAI-2004): Sixteenth Innovative Applications of Artificial Intelligence Conference (IAAI-2004)

Y2 - 25 July 2004 through 29 July 2004

ER -

Regression with respect to sensing actions and partial states

Abstract

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ASJC Scopus subject areas

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