We present a framework for decision making under uncertainty where the priorities of the alternatives can depend on the situation at hand. We design a logic-programming language, D...
Abstract. Ordered Choice Logic Programming (OCLP) allows for dynamic preference-based decision-making with multiple alternatives without the need for any form of negation. This com...
We present a framework for decision making with the possibility to express circumstance-dependent preferences among different alternatives for a decision. This new formalism, Order...
Abstract. Ordered Choice Logic Programming (OCLP) allows for preferencebased decision-making with multiple alternatives without the burden of any form of negation. This complete ab...
Abstract. There is currently a large interest in probabilistic logical models. A popular algorithm for approximate probabilistic inference with such models is Gibbs sampling. From ...