Efficient Reasoning in Regular Boardgames
  We present the technical side of reasoning in Regular Boardgames (RBG)
language -- a universal General Game Playing (GGP) formalism for the class of
finite deterministic games with perfect information, encoding rules in the form
of regular expressions. RBG serves as a research tool that aims to aid in the
development of generalized algorithms for knowledge inference, analysis,
generation, learning, and playing games. In all these tasks, both generality
and efficiency are important.
  In the first part, this paper describes optimizations used by the RBG
compiler. The impact of these optimizations ranges from 1.7 to even 33-fold
efficiency improvement when measuring the number of possible game playouts per
second. Then, we perform an in-depth efficiency comparison with three other
modern GGP systems (GDL, Ludii, Ai Ai). We also include our own highly
optimized game-specific reasoners to provide a point of reference of the
maximum speed. Our experiments show that RBG is currently the fastest among the
abstract general game playing languages, and its efficiency can be competitive
to common interface-based systems that rely on handcrafted game-specific
implementations. Finally, we discuss some issues and methodology of computing
benchmarks like this.
