TY - GEN
T1 - Abstract planning with unknown object quantities and properties
AU - Srivastava, Siddharth
AU - Immerman, Neil
AU - Zilberstein, Shlomo
PY - 2009
Y1 - 2009
N2 - State abstraction has been widely used for state aggregation in approaches to AI search and planning. In this paper we use a powerful abstraction technique from software model checking for representing collections of states with different object quantities and properties. We exploit this method to develop precise abstractions and action operators for use in AI. This enables us to find scalable, algorithm-like plans with branches and loops which can solve problems of unbounded sizes. We describe how this method of abstraction can be effectively used in AI, with compelling results from implementations of two planning algorithms.
AB - State abstraction has been widely used for state aggregation in approaches to AI search and planning. In this paper we use a powerful abstraction technique from software model checking for representing collections of states with different object quantities and properties. We exploit this method to develop precise abstractions and action operators for use in AI. This enables us to find scalable, algorithm-like plans with branches and loops which can solve problems of unbounded sizes. We describe how this method of abstraction can be effectively used in AI, with compelling results from implementations of two planning algorithms.
UR - http://www.scopus.com/inward/record.url?scp=84862705530&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84862705530&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84862705530
SN - 9781577354338
T3 - SARA 2009 - Proceedings, 8th Symposium on Abstraction, Reformulation and Approximation
SP - 143
EP - 150
BT - SARA 2009 - Proceedings, 8th Symposium on Abstraction, Reformulation and Approximation
T2 - 8th Symposium on Abstraction, Reformulation and Approximation, SARA 2009
Y2 - 7 July 2009 through 10 July 2009
ER -