Abstract. Possibilistic knowledge bases gather propositional formulas associated with degrees belonging to a linearly ordered scale. These degrees reflect certainty or priority, de...
Abstract. We propose a machine learning approach to action prediction in oneshot games. In contrast to the huge literature on learning in games where an agent's model is deduc...
We propose a logic for specifying security policies at a very el of abstraction. The logic accommodates the subjective nature of affirmations for authorization and knowledge withou...
Deepak Garg, Lujo Bauer, Kevin D. Bowers, Frank Pf...
Abstract. Aiming to build a complete benchmark for better evaluation of existing ontology systems, we extend the well-known Lehigh University Benchmark in terms of inference and sc...
Li Ma, Yang Yang, Zhaoming Qiu, Guo Tong Xie, Yue ...
Parallel performance tuning naturally involves a diagnosis process to locate and explain sources of program inefficiency. Proposed is an approach that exploits parallel computation...