Second you really need to understand and fine tune cuts, and other search optimization primitives.
Finally in what concerns Game AIs, it is a mixture of algorithms and heuristics, a single paradigm language (first order logic) like Prolog, can't be a tool for all nails.
In the Classsic AI course we had to implement gaming AI algorithms (A*, alpha-beta pruning, etc) and in Prolog for one specific assignment. After trying for a while, I got frustrated and asked the teacher if I could do it in Ruby instead. He agreed: he was the kind of person who just couldn't say no, he was too nice for his own good. I still feel bad about it.
Rest In Peace, Alexandre.
I know you likely mean regular Prolog, but that's actually fairly easy and intuitive to reason with (code dependent). Lambda Prolog is much, much harder to reason about IMO and there's a certain intractability to it because of just how complex the language is.
Implementing other programming languages and proving theorems are the low-hanging fruits since you get variable binding without name management, but I genuinely think it has profound implications for expert systems since it essentially removes a massive amount of complexity from contextual reasoning. Being able to account for patient history when providing a diagnosis, for example.