---
res:
  bibo_abstract:
  - POMDPs are standard models for probabilistic planning problems, where an agent
    interacts with an uncertain environment. We study the problem of almost-sure reachability,
    where given a set of target states, the question is to decide whether there is
    a policy to ensure that the target set is reached with probability 1 (almost-surely).
    While in general the problem is EXPTIMEcomplete, in many practical cases policies
    with a small amount of memory suffice. Moreover, the existing solution to the
    problem is explicit, which first requires to construct explicitly an exponential
    reduction to a belief-support MDP. In this work, we first study the existence
    of observation-stationary strategies, which is NP-complete, and then small-memory
    strategies. We present a symbolic algorithm by an efficient encoding to SAT and
    using a SAT solver for the problem. We report experimental results demonstrating
    the scalability of our symbolic (SAT-based) approach. © 2016, Association for
    the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Krishnendu
      foaf_name: Chatterjee, Krishnendu
      foaf_surname: Chatterjee
      foaf_workInfoHomepage: http://www.librecat.org/personId=2E5DCA20-F248-11E8-B48F-1D18A9856A87
    orcid: 0000-0002-4561-241X
  - foaf_Person:
      foaf_givenName: Martin
      foaf_name: Chmelik, Martin
      foaf_surname: Chmelik
      foaf_workInfoHomepage: http://www.librecat.org/personId=3624234E-F248-11E8-B48F-1D18A9856A87
  - foaf_Person:
      foaf_givenName: Jessica
      foaf_name: Davies, Jessica
      foaf_surname: Davies
      foaf_workInfoHomepage: http://www.librecat.org/personId=378E0060-F248-11E8-B48F-1D18A9856A87
  bibo_doi: 10.1609/aaai.v30i1.10422
  bibo_volume: 2016
  dct_date: 2016^xs_gYear
  dct_language: eng
  dct_publisher: AAAI Press@
  dct_title: A symbolic SAT based algorithm for almost sure reachability with small
    strategies in POMDPs@
...