Results 1 -
3 of
3
Discovering planning invariants as anomalies in state descriptions
- In ICAPS-05
, 2005
"... Planning invariants are formulae that are true in every reachable state of a planning world. We describe a novel approach to the problem of discovering such invariants—by analyzing only a reachable state of the planning domain, and not its operators. Our system works by exploiting perceived patterns ..."
Abstract
-
Cited by 2 (1 self)
- Add to MetaCart
(Show Context)
Planning invariants are formulae that are true in every reachable state of a planning world. We describe a novel approach to the problem of discovering such invariants—by analyzing only a reachable state of the planning domain, and not its operators. Our system works by exploiting perceived patterns and anomalies in the state description: It hypothesizes that patterns that are very unlikely to have arisen by chance represent features of the planning world. We demonstrate that the number and types of laws we discover are comparable to those discovered by a system that uses complete operator descriptions in addition to a state description.
State-based discovery and verification of propositional invariants
- Proceedings of the 2006 International Conference on Artificial Intelligence. CSREA Press, Las Vegas, NV
, 2005
"... Planning invariants are formulae that are true in every reachable state of a planning world. We describe a novel approach to the problem of discovering such invariants in propositional form—by analyzing only a set of reachable states of the planning domain, and not its operators. Our system works by ..."
Abstract
-
Cited by 1 (1 self)
- Add to MetaCart
(Show Context)
Planning invariants are formulae that are true in every reachable state of a planning world. We describe a novel approach to the problem of discovering such invariants in propositional form—by analyzing only a set of reachable states of the planning domain, and not its operators. Our system works by exploiting perceived patterns of propositional covariance across the set of states: It hypothesizes that strongly-defined patterns represent features of the planning world. We demonstrate that, in practice, our system overwhelmingly produces correct invariants. Moreover, we compare it with a well-known system from the literature that uses complete operator descriptions, and show that it discovers a comparable number of invariants, and moreover, does so orders of magnitude faster. We also show how an existing operator-based invariant finder can be used to verify the correctness of the invariants we find, should operator information be available. We show that such hybrid systems can efficiently produce verifiably true invariants.
Discovering Planning Invariants as Anomalies in State Descriptions
"... Planning invariants are formulae that are true in every reachable state of a planning world. We describe a novel approach to the problem of discovering such invariants—by analyzing only a reachable state of the planning domain, and not its operators. Our system works by exploiting perceived patterns ..."
Abstract
- Add to MetaCart
(Show Context)
Planning invariants are formulae that are true in every reachable state of a planning world. We describe a novel approach to the problem of discovering such invariants—by analyzing only a reachable state of the planning domain, and not its operators. Our system works by exploiting perceived patterns and anomalies in the state description: It hypothesizes that patterns that are very unlikely to have arisen by chance represent features of the planning world. We demonstrate that the number and types of laws we discover are comparable to those discovered by a system that uses complete operator descriptions in addition to a state description.
