| dc.contributor.advisor |
Leslie Kaelbling |
en_US |
| dc.contributor.author |
Gardiol, Natalia H. |
en_US |
| dc.contributor.author |
Kaelbling, Leslie Pack |
en_US |
| dc.contributor.other |
Learning and Intelligent Systems |
en_US |
| dc.date.accessioned |
2008-08-01T21:30:16Z |
|
| dc.date.available |
2008-08-01T21:30:16Z |
|
| dc.date.issued |
2008-07-29 |
en_US |
| dc.identifier.other |
MIT-CSAIL-TR-2008-050 |
en_US |
| dc.identifier.uri |
http://hdl.handle.net/1721.1/41920 |
|
| dc.description.abstract |
We describe a method to use structured representations of the environment’s dynamics to constrain and speed up the planning process. Given a problem domain described in a probabilistic logical description language, we develop an anytime technique that incrementally improves on an initial, partial policy. This partial solution is found by ï¬rst reducing the number of predicates needed to represent a relaxed version of the problem to a minimum, and then dynamically partitioning the action space into a set of equivalence classes with respect to this minimal representation. Our approach uses the envelope MDP framework, which creates a Markov decision process out of a subset of the full state space as de- termined by the initial partial solution. This strategy permits an agent to begin acting within a restricted part of the full state space and to expand its envelope judiciously as resources permit. |
en_US |
| dc.description.provenance |
Submitted by CSAIL Importer (publications-dspace@csail.mit.edu) on 2008-08-01T21:30:14Z
No. of bitstreams: 2
MIT-CSAIL-TR-2008-050.pdf: 711777 bytes, checksum: d223593062cbd5fd386a158ec0311320 (MD5)
MIT-CSAIL-TR-2008-050.ps: 73870 bytes, checksum: 0afe9e7c8a0b1feb188c9753c690f202 (MD5) |
en |
| dc.description.provenance |
Made available in DSpace on 2008-08-01T21:30:16Z (GMT). No. of bitstreams: 2
MIT-CSAIL-TR-2008-050.pdf: 711777 bytes, checksum: d223593062cbd5fd386a158ec0311320 (MD5)
MIT-CSAIL-TR-2008-050.ps: 73870 bytes, checksum: 0afe9e7c8a0b1feb188c9753c690f202 (MD5)
Previous issue date: 2008-07-29 |
en |
| dc.format.extent |
17 p. |
en_US |
| dc.relation |
Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory |
en_US |
| dc.relation |
|
en_US |
| dc.title |
Adaptive Envelope MDPs for Relational Equivalence-based Planning |
en_US |
