RVRL (Rule Value Reinforcement Learning) is a new algorithm which extends an existing learning framework that models the environment of a situated agent using a probabilistic rule...
- Power estimation in combinational modules is addressed from a probabilistic point of view. The zero-delay hypothesis is considered and under highly correlated input streams, the ...
We describe a new algorithm for proving temporal properties expressed in LTL of infinite-state programs. Our approach takes advantage of the fact that LTL properties can often be...
We study the type checking and type inference problems for intuitionistic linear logic: given a System F typed λ-term, (i) for an alleged linear logic type, determine whether the...
Narrowing-driven partial evaluation is a powerful technique for the specialization of (first-order) functional and functional logic programs. However, although it gives good resu...