When intelligent systems reason about complex problems with a large hierarchical classification space it is hard to evaluate system performance. For classification problems, differ...
POMDPs are a popular framework for representing decision making problems that contain uncertainty. The high computational complexity of finding exact solutions to POMDPs has spaw...
We address the problem of answering conjunctive queries over knowledge bases, specified by sets of first-order sentences called tuple-generating dependencies (TGDs). This problem i...
In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
The algorithm presented here, BCC, is an enhancement of the well known Backtrack used to solve constraint satisfaction problems. Though most backtrack improvements rely on propaga...