Flexible FOND Planning with Explicit Fairness Assumptions
  We consider the problem of reaching a propositional goal condition in
fully-observable non-deterministic (FOND) planning under a general class of
fairness assumptions that are given explicitly. The fairness assumptions are of
the form A/B and say that state trajectories that contain infinite occurrences
of an action a from A in a state s and finite occurrence of actions from B,
must also contain infinite occurrences of action a in s followed by each one of
its possible outcomes. The infinite trajectories that violate this condition
are deemed as unfair, and the solutions are policies for which all the fair
trajectories reach a goal state. We show that strong and strong-cyclic FOND
planning, as well as QNP planning, a planning model introduced recently for
generalized planning, are all special cases of FOND planning with fairness
assumptions of this form which can also be combined. FOND+ planning, as this
form of planning is called, combines the syntax of FOND planning with some of
the versatility of LTL for expressing fairness constraints. A new planner is
implemented by reducing FOND+ planning to answer set programs, and the
performance of the planner is evaluated in comparison with FOND and QNP
planners, and LTL synthesis tools.
