Constraint Programming is an attractive approach for solving AI planning problems by modelling them as Constraint Satisfaction Problems (CSPs). However, formulating effective cons...
Andrea Rendl, Ian Miguel, Ian P. Gent, Peter Grego...
We present a new planning algorithm that formulates the planning problem as a counting satisfiability problem in which the number of available solutions guides the planner determ...
Enforced hill-climbing is an effective deterministic hillclimbing technique that deals with local optima using breadth-first search (a process called "basin flooding"). ...
In intelligence analysis, information plays an important role in solving problems and making decisions. However, an increasing number of malicious behaviors, most of which come fr...
Eugene Santos Jr., Hien Nguyen, Fei Yu, Keum Joo K...
We study computational problems that arise in the context of iterated dominance in anonymous games, and show that deciding whether a game can be solved by means of iterated weak d...