Zusammenfassung: We study the performance of DPLL algorithms on parameterized problems. In particular, we investigate how difficult it is to decide whether small solutions exist for satisfiability and other combinatorial problems. For this purpose we develop a Prover-Delayer game which models the running time of DPLL procedures and we establish an information-theoretic method to obtain lower bo...

Selecting appropriate features has become a key task when dealing with high-dimensional data. We present a new algorithm designed to find an optimal solution for classification tasks. Our approach combines forward selection, backward elimination and exhaustive search. We demonstrate its capabilities and limits using artificial and real world data sets. Regarding artificial data sets interleavin...

Social agents and robots will require both learning and emotional capabilities to successfully enter society. This paper connects both challenges, by studying models of emotion generation in sequential decision-making agents. Previous work in this field has focussed on model-free reinforcement learning (RL). However, important emotions like hope and fear need anticipation, which requires a mode...

Perimeter search is a bidirectional search algorithm consisting of two phases. In the first phase, a limited regression search computes the perimeter, a region which must necessarily be passed in every solution. In the second phase, a heuristic forward search finds an optimal plan from the initial state to the perimeter. The drawback of perimeter search is the need to compute heuristic estimate...

Most symbolic bug detection techniques perform search over the program control flow graph based on either forward symbolic execution or backward weakest preconditions computation. The complexity of determining interprocedural all-path feasibility makes it difficult for such analysis to judge upfront whether the behavior of a particular caller or callee procedure is relevant to a given property ...

The Weibull distribution is widely employed in several areas of engineering because it is an extremely flexible distribution with different shapes. Moreover, it can include characteristics of several other distributions. However, successful usage of Weibull distribution depends on estimation accuracy for three parameters of scale, shape and location. This issue shifts the attentions to the requ...