In Defence of Design Patterns for AI Planning Knowledge Models

Mauro Vallati; Lee McCluskey

In Defence of Design Patterns for AI Planning Knowledge Models

Research output: Contribution to journal › Conference article › peer-review

Abstract

Design patterns are widely used in various areas of computer science, the most notable example being software engineering. They have been introduced also for supporting the encoding of automated planning knowledge models, but with little success. In this paper, we argue about the merits of design patterns, as an example of the broader class of reusable abstractions, in the automated planning context; particularly, we aim at drawing attention to their potential usefulness for the explainability of domain-independent planning systems.

Original language	English
Number of pages	7
Journal	CEUR Workshop Proceedings
Volume	2745
Publication status	Published - 19 Nov 2020
Event	Joint 8th Italian Workshop on Planning and Scheduling and the 27th International Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion - Virtual, Online Duration: 25 Nov 2020 → 27 Nov 2020 Conference number: 8 & 27

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title = "In Defence of Design Patterns for AI Planning Knowledge Models",

abstract = "Design patterns are widely used in various areas of computer science, the most notable example being software engineering. They have been introduced also for supporting the encoding of automated planning knowledge models, but with little success. In this paper, we argue about the merits of design patterns, as an example of the broader class of reusable abstractions, in the automated planning context; particularly, we aim at drawing attention to their potential usefulness for the explainability of domain-independent planning systems.",

keywords = "Automated Planning, Design Patterns, Explainability, Knowledge Engineering",

author = "Mauro Vallati and Lee McCluskey",

year = "2020",

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day = "19",

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note = "Joint 8th Italian Workshop on Planning and Scheduling and the 27th International Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion, IPS-RCRA 2020 ; Conference date: 25-11-2020 Through 27-11-2020",

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TY - JOUR

T1 - In Defence of Design Patterns for AI Planning Knowledge Models

AU - Vallati, Mauro

AU - McCluskey, Lee

N1 - Conference code: 8 & 27

PY - 2020/11/19

Y1 - 2020/11/19

N2 - Design patterns are widely used in various areas of computer science, the most notable example being software engineering. They have been introduced also for supporting the encoding of automated planning knowledge models, but with little success. In this paper, we argue about the merits of design patterns, as an example of the broader class of reusable abstractions, in the automated planning context; particularly, we aim at drawing attention to their potential usefulness for the explainability of domain-independent planning systems.

AB - Design patterns are widely used in various areas of computer science, the most notable example being software engineering. They have been introduced also for supporting the encoding of automated planning knowledge models, but with little success. In this paper, we argue about the merits of design patterns, as an example of the broader class of reusable abstractions, in the automated planning context; particularly, we aim at drawing attention to their potential usefulness for the explainability of domain-independent planning systems.

KW - Automated Planning

KW - Design Patterns

KW - Explainability

KW - Knowledge Engineering

UR - http://www.scopus.com/inward/record.url?scp=85096995638&partnerID=8YFLogxK

UR - http://ceur-ws.org/Vol-2745/

M3 - Conference article

AN - SCOPUS:85096995638

VL - 2745

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

T2 - Joint 8th Italian Workshop on Planning and Scheduling and the 27th International Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion

Y2 - 25 November 2020 through 27 November 2020

ER -

In Defence of Design Patterns for AI Planning Knowledge Models

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