Many testing and analysis techniques have been developed for inhouse use. Although they are effective at discovering defects before a program is deployed, these techniques are oft...
We consider programming language aspects of algorithms that operate on data too large to fit into memory. In previous work we have introduced IntML, a functional programming langu...
Abstract. Approximate dynamic programming offers a new modeling and algorithmic strategy for complex problems such as rail operations. Problems in rail operations are often modeled...
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...
We present the Genetic L-System Programming (GLP) paradigm for evolutionary creation and development of parallel rewrite systems (Lsystems, Lindenmayer-systems) which provide a com...