: Decision-support systems that help solving problems in open and weak theory domains, i.e. hard problems, need improved methods to ground their models in real world situations. Mo...
We define the Tight Semantics (TS), a new semantics for all NLPs complying with the requirements of: 2-valued semantics; preserving the models of SM; guarantee of model existence...
Traditional Machine Learning approaches based on single inference mechanisms have reached their limits. This causes the need for a framework that integrates approaches based on aba...
We study the automated verification of pointer safety for heap-manipulating imperative programs with unknown procedure calls. Given a Hoare-style partial correctness specificati...
As we face the real possibility of modelling agent systems capable of non-deterministic self-evolution, we are confronted with the problem of having several different possible futu...