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Content Provider | ACM Digital Library |
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Author | Parmar, Aarati |
Abstract | Heuristic search planners are so far the most successful. Almost all use as their heuristic an estimate of the distance to a goal state. We formalize a logical measure of progress, defined as a predicate P(x,s) true of objects x at a situation s. Actions which increase P's extension are guaranteed to move closer to a goal situation, so that P enables us to form plans without search. One example of a measure of progress is the concept of final position Used in BlocksWorld. It is not clear how to find a P for an arbitrary domain, so instead we identify three different classes of domains and conditions which allow us to construct a measure of progress.An obvious P will not deliver optimal plans, but it should encode plans which are "good enough" Our paradigm is entirely within first-order logic, allowing us to extend our results to concurrent domains and those containing non-trivial state constraints. It turns out P not only encodes goal orderings, but subgoal orderings. P also gives rise to a strategy function a(s) which can be used to create a universal (complete) teleo-reactive (TR) program. Given the fact that P-increasing actions will never require backtracking, this TR program can be a powerful on-line planner. |
Starting Page | 498 |
Ending Page | 505 |
Page Count | 8 |
ISBN | 0262511290 |
Language | English |
Publisher | Association for Computing Machinery (ACM) |
Publisher Date | 2002-07-28 |
Access Restriction | Subscribed |
Content Type | Text |
Resource Type | Article |
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