Prolog is actually a perfect fit for all kinds of adventure, role playing, strategy, and classic board/card games, with clauses representing game rules and facts representing the game state and universe in the most natural way.

Simple general-purpose opponents can be coded using just recursive backtracking search, while more advanced ones (supporting moves that need to destructively change state) can still be conveniently modelled by reifying facts and thereby enable backtracking over assert/retract-like Prolog DB modifications, as used in discrete combinatorial planners [1].

[1]: https://quantumprolog.sgml.net/container-planning-demo/part1...

All examples shown in the article can be ran with Datalog too (with stratified negation and arithmetic comparison), which has a clearer execution model and looks almost identical to Prolog. Prolog underneath is doing backtracking, while Datalog is finding a least fixed point of derived relations where iterating on data won't produce more relations, and is akind to SQL (but usually stronger because of recursion).