Anthony Barrett and Daniel Weld, TaskDecomposition via plan parsing, Proceedings of the National Conference on Arti cial Intelligence (AAAI), 1994, 1117-1122.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....decompositions provide the planner with search control knowledge. In particular, the decompositions eliminate a large number of physically feasible primitive action sequences, much like the search control formulas used in this work. This view of HTN planners was made very clear by Barrett and Weld [8] who showed how the specified task decompositions could be used to prune partially ordered plans composed of primitive actions. The pruning was accomplished with a parsing algorithm. The language and representation used by HTN planners for their control knowledge is quite distinct from that ....

A. Barrett and D. Weld. Task-decomposition via plan parsing. In Proceedings of the AAAI National Conference, pages 1117--1122, 1994.

.... task reduction planners: task reduction schemas (non primitive operators) contain plan fragments, supplied by the domain modeller, that remove search during planning (this HTN framework, in the tradition of NOAH [51] has recently been formalised and compared to partial order planners by [22] and [4] for example) We argue that our macros serve the same function: they have the same hierarchical flavour as task reduction schemas since they are sort abstracted; and unlike other examples of macro use they do not heavily increase the branching factor during planning because macro selection and ....

.... development of this new planner will involve experimentation using sort engineered compiled domain models with other plan generation algorithms such as HTN, a hierarchical planner in the tradition of NOAH [51] which has recently been formalised and compared to partial order planners by [22] and [4]. This appears a promising area of investigation since the macros that are generated by our compilation tools can be seen as storing abstract planning solutions, and as such they could provide solutions for a hierarchical planner at levels organised by sort abstraction. Alternatively, the use of ....

A. Barrett and D. S. Weld. Task-Decomposition via Plan Parsing. In Twelfth National Conference on Artificial Intelligence, 1994. 60

....a user s (domain writer s) prescriptions about what constitute good plans. Informally, the only acceptable solutions are those that not only achieve the top level goals upon execution, but can also be parsed in terms of the non primitive actions that are provided to support those top level goals [2] . We also say that such solutions respect (preserve) user intent. As an example, in the travel domain, although hitch hiking or traveling without tickets are possible ways of achieving an At(x) goal, they can not be parsed in terms of the Gobybus or Gobytrain non primitive actions that are ....

....template in Figure 1 would be to leave all refinements as they are, and add an extra filter to the consistency check to prune partial plans that cannot be parsed in terms of the non primitive actions. This approach, that we can call bottom up HTN planning, has been advocated by Barrett and Weld [2] . ing step t 0 . As part of the establishment, t 0 is constrained to precede t, and is forced to give c (if c is a conditional effect, this involves adding the causation precondition of c as a precondition to t 0 [18] Optionally, IPCs of the form (t 0 c Gamma t) are posted to ....

A. Barrett and D. Weld. Task Decomposition via Plan Parsing. In Proc. AAAI-94.

....on operators. However, constraints in Collage related actions to other actions, while constraints in operator construction apply to the operator itself. Another related family of planners to describe are hierarchical task networks, HTN s) Sacerdoti, 1990, Wilkins, 1990, Erol et al. 1994, Barrett and Weld, 1994] which act by decomposing a high level task into lower level tasks, eventually leading to primitive level actions which can be performed directly. This process of hierarchical task decomposition is distinct from operator construction. Operator construction refines individual operator ....

Barrett, A. and Weld, D. S. (1994). Task decomposition via plan parsing. In Proceedings of the twelth National Conference on Artificial Intelligence, pages 1117--1122, Seattle.

.... used in plan recognition research (e.g. Alexandersson 95, Ardissono Cohen 95, Lin 95, Lin Goebel 90, Vilain 90, Wobcke 94] In Kautz s framework, the plans and goals the actor might have are stored in an input event hierarchy, similar to those used in hierarchical planning [Sacerdoti 77, Barrett Weld 94] The event hierarchy describes all the behavior that people might exhibit in some particular domain. Figure 2.1 shows a sample event hierarchy, taken from Kautz s thesis. Each node in the hierarchy represents an event that can occur, such as getting a gun or robbing a bank. Events can be ....

A. Barrett and D. Weld. Task-decomposition via plan parsing. In Proc. 12th Nat. Conf. AI, July 1994. Available at ftp://ftp.cs.washington. edu/pub/ai/.

....the i n ova model set the space within which a plan may be further constrained. The issues and ova constraints restrict the plans within that space which are valid. Recently, formal representations have begun to address issues of realistic plan representations and to model hierarchical planning [2], 12] 13] 26] In particular, Kambhampati has described a formal truth criterion for plans which are represented with greater levels of realism. He describes plans as a 5 tuple [11] S, O, B, ST, L S a set of plan steps or nodes ST a symbol table mapping each plan step or node to a domain ....

Barrett, A. and Weld, D.S., Task-Decomposition via Plan Parsing, Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), Seattle, USA, 1994.

....on goal achievement aspects of planners in a simplified environment that is not representative of the approaches actually taken in practical planners. Recently however, formal representations have begun to address issues of realistic plan representations and to model hierarchical planning [4], 18] 22] 38] In particular, Kambhampati has described a formal truth criterion for plans which are represented with greater levels of realism. He describes plans as a 5 tuple [16] S, O, B, ST, L S a set of plan steps or nodes ST a symbol table mapping each plan step or node to a domain ....

Barrett, A. and Weld, D.S., Task-Decomposition via Plan Parsing, Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), Seattle, USA, 1994.

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A. Barrett and D. Weld. Task-decomposition via plan parsing. In Proc. 12th Nat. Conf. on A.I., July 1994. Available via FTP from pub/ai/ at ftp.cs.washington.edu.

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Barrett, A., and Weld, D. 1994b. Taskdecomposition via plan parsing. In Proc. 12th Nat.

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Barrett, A., & Weld, D. (1994b). Task-decomposition via plan parsing. In Proc. 12th Nat.

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Anthony Barrett and Daniel Weld, TaskDecomposition via plan parsing, Proceedings of the National Conference on Arti cial Intelligence (AAAI), 1994, 1117-1122.

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Anthony Barrett and Daniel Weld, Task-Decomposition 15 via plan parsing, Proceedings of the National Conference on Arti cial Intelligence (AAAI), 1994, 1117-1122.

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A. Barrett and D. Weld. Task Decomposition via Plan Parsing. In Proc. AAAI-94.

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A. Barrett and D. Weld. Task-decomposition via plan parsing. In Proceedings of the AAAI National Conference, pages 1117--1122, 1994.

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Anthony Barrett and Daniel Weld, Task-Decomposition via plan parsing, Proceedings of the National Conference on Artificial Intelligence (AAAI), 1994, 1117-1122.

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Barrett, A. and Weld, D.S., TaskDecomposition via Plan Parsing, Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), Seattle, USA, 1994.

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Anthony Barrett and Daniel Weld, TaskDecomposition via plan parsing, Proceedings of the National Conference on Artificial Intelligence (AAAI), 1994, 1117-1122.

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