Symbolic planning in belief space

SASY (Scalable and Adjustable SYmbolic) Planner is a flexible symbolic planner which searches for a satisfying plan to a partially observable Markov decision process, or a POMDP, while benefiting from advantages of classical symbolic planning such as compact belief state expression, domain-independent heuristics, and structural simplicity. Belief space symbolic formalism, an extension of classical symbolic formalism, can be used to transform probabilistic problems into a discretized and deterministic representation such that domain-independent heuristics originally created for classical symbolic planning systems can be applied to them. SASY is optimized to solve POMDPs encoded in belief space symbolic formalism, but can also be used to find a solution to general symbolic planning problems. We compare SASY to two other POMDP solvers, SARSOP and POMDPX_NUS, and define a new benchmark domain called Elevator.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2015

Author dc:creator

• Kamahele-Sanfratello, Ciara L. (Ciara Lei)

Advisor dc:contributor.advisor

• Leslie Pack Kaelbling.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/100604

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/100604