Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Grounding is the task of reducing a first-order theory and finite domain to an equivalent propositional theory. It is used as preprocessing phase in many logic-based reasoning s...
Random problem distributions have played a key role in the study and design of algorithms for constraint satisfaction and Boolean satisfiability, as well as in our understanding o...
Developing software from models is a growing practice and there exist many model-based tools (e.g., model editors, model interpreters) for supporting model-driven engineering. Eve...
Tomaz Lukman, Marjan Mernik, Zekai Demirezen, Barr...
Blocks World (BW) has been one of the most popular model domains in AI history. However, there has not been serious work on axiomatizing the state constraints of BW and giving jus...