A Conflict-Driven Approach for Reaching Goals Specified with Negation as Failure
Keywords: goal specification, answer set programming, logic, reinforcement learning, conflict-driven
TL;DR: Specifying goals with negation as failure can be very efficient when combined with conflict-driven search.
Abstract: First-order logic allows for the expressive specification of goals. Using negation as failure, one can specify what must not be true in a goal state instead of what must be true, which can result in succinct goal specifications while also being computationally advantageous. However, due to non-monotonicity, integration of negation as failure and recent deep reinforcement learning methods that incorporate first-order logic in goal specification can be cumbersome. To address this problem, we create a conflict-driven algorithm for non-monotonic goal specification that refines search for a goal state based on conflicts encountered during search. Our results show that this conflict-driven approach results in significantly shorter paths and can significantly speed up search when compared to not taking conflicts into consideration. Furthermore, our results show that finding paths to goals can be much more efficient when goals are specified with negation as failure instead of without negation as failure.
Submission Number: 4
Loading