Integrating Electrical and Mechanical Design and Process Planning

Smith, Stephen J. J.; Hebbar, Kiran; Nau, Dana S.; Minis, Ioannis

doi:10.1007/978-0-387-35192-6_17

Cited by 7 publications

(4 citation statements)

References 10 publications

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“…Historically, most of the HTN-planning researchers have focused on practical applications. Examples include production-line scheduling (Wilkins, 1988), crisis management and logistics (Currie & Tate, 1991;Tate, Drabble, & Kirby, 1994;Biundo & Schattenberg, 2001), planning and scheduling for spacecraft (Aarup, Arentoft, Parrod, Stader, & Stokes, 1994;Estlin, Chien, & Wang, 1997), equipment configuration (Agosta, 1995), manufacturability analysis (Hebbar, Smith, Minis, & Nau, 1996;Smith, Hebbar, Nau, & Minis, 1997), evacuation planning (Muñoz-Avila, Aha, Nau, Weber, Breslow, & Yaman, 2001), and the game of bridge (Smith, Nau, & Throop, 1998a, 1998b.…”

Section: Htn Planningmentioning

confidence: 99%

SHOP2: An HTN Planning System

Nau¹,

Au²,

Ilghami³

et al. 2003

jair

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674

392

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Section: Htn Planningmentioning

confidence: 99%

SHOP2: An HTN Planning System

Nau¹,

Au²,

Ilghami³

et al. 2003

jair

Self Cite

674

392

View full text Add to dashboard Cite

show abstract

“…Historically, most of the HTN planning research has focused on specific application domains. Examples include production-line scheduling [Wilkins, 1988], crisis management and logistics [Currie and Tate, 1991, Tate et al, 1994, Biundo and Schattenberg, 2001], planning and scheduling for spacecraft [Aarup et al, 1994, Estlin et al, 1997, equipment configuration [Agosta, 1995], manufacturability analysis [Hebbar et al, 1996, Smith et al, 1997, evacuation planning , and the game of bridge [Smith et al, 1998a, Smith et al, 1998b. However, there are several domain-independent HTN planning systems, such as Nonlin [Tate, 1977], Sipe-2 [Wilkins, 1990], OPlan [Currie andTate, 1991, Tate et al, 1994], UMCP [Erol et al, 1994], SHOP [Nau et al, 1999], ASHOP [Dix et al, 2003, Dix et al, 2002, and SHOP2 [Nau et al, 2001].…”

Section: Introductionmentioning

confidence: 99%

Planning in Answer Set Programming Using Ordered Task Decomposition

Dix

Kuter

Nau

2003

KI 2003: Advances in Artificial Intelligence

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In this paper we investigate a formalism for solving planning problems based on ordered task decomposition using Answer Set Programming (ASP). Our planning methodology is an adaptation of Hierarchical Task Network (HTN) planning, an approach that has led to some very efficient planners. The ASP paradigm evolved out of the stable semantics for logic programs in recent years and is strongly related to nonmonotonic logics. It also led to various very efficient implementations (Smodels, DLV ). While all previous approaches for using ASP for planning rely on action-based planning, we consider for the first time a formulation of HTN planning as described in the SHOP planning system and define a systematic translation method from SHOP 's representation of the planning problem into logic programs with negation. We show that our translation is sound and complete: answer sets of the logic program obtained by our translation correspond exactly to the solutions of the planning problem. Our approach does not rely on a particular system for computing answer sets and serves several purposes. (1) It constitutes a means to evaluate ASP systems by using well-established benchmarks from the planning community. (2) It makes the more expressive HTN planning available in ASP. (3) When our approach is implemented on ASP solvers, its time requirement appears to grow no faster than roughly proportional to that of a dedicated HTN planning system (SHOP ). (4) It outperforms the transformation of an STRIPS-style planning problem into ASP proposed in [Son et al., 2001]. The particular relevance of that transformation method to our work is that, in their work, [Son et al., 2001] proposed to use a form of control knowledge to speed up the classical planning process. In this paper, we show that HTN control knowledge provides more time-efficient transformations compared to the control strategies presented in [Son et al., 2001].

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“…The IPPD tool described in this paper grew out of the merger of two previous projects at the University of Maryland: the EDAPS project (Hebbar et al 1996, Smith et al 1997) and the EXTRA project (Kame, et al 1998).…”

Section: Our Prior Workmentioning

confidence: 99%

Integrated Product and Process Design of Microwave Modules Using AI Planning and Integer Programming

Nau

Ball²,

Baras³

et al. 2002

From Knowledge Intensive CAD to Knowledge Intensive Engineering

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Abstract:This paper describes the process planning techniques we developed for use in an Integrated Product and Process Design (IPPD) tool for the design and manufacture of microwave transmit/receive modules. Given a collection of data about the design of a microwave module, the IPPD tool uses a combination of AI planning and optimization-based tradeoff analysis to produce a collection of alternative designs and alternative process plans that have Pareto optimal values for manufacturing and purchasing lead time, process yield, cost, and number of suppliers. The IPPD tool provides a GUI for generating and examining these alternatives in real time, to help users modify the design to improve its cost and productivity.

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Integrating Electrical and Mechanical Design and Process Planning

Cited by 7 publications

References 10 publications

SHOP2: An HTN Planning System

SHOP2: An HTN Planning System

Planning in Answer Set Programming Using Ordered Task Decomposition

Integrated Product and Process Design of Microwave Modules Using AI Planning and Integer Programming

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