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2001
Springer

Effect of knowledge representation on model based planning: experiments using logic programming encodings

10 years 2 months ago
Effect of knowledge representation on model based planning: experiments using logic programming encodings
In this paper we implement planning using answer set programming. We consider the action language A and its extensions. We show that when the domain is described using richer features such as qualification, ramification and conditional effects not only the encoding is smaller, but also it takes less time to find a plan. We also show that encoding of Bacchus and Kabanza's style temporal constraints is fairly straightforward in answer set planning. Finally, unlike other model enumeration planning encodings, in our encoding we can just give an upper bound of the length of the plan, instead of the exact length. We illustrate the above features using the blocks world example from the AIPS planning contests.
Le-Chi Tuan, Chitta Baral
Added 23 Aug 2010
Updated 23 Aug 2010
Type Conference
Year 2001
Where ASP
Authors Le-Chi Tuan, Chitta Baral
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