Reasoning about string variables, in particular program inputs, is an important aspect of many program analyses and testing frameworks. Program inputs invariably arrive as strings...
Abstract. Adaptive consistency is a solving algorithm for constraint networks. Its basic step is variable elimination: it takes a network as input, and producesan equivalent networ...
— This paper proposes an optimal gait generation framework using virtual constraint and learning optimal control. In this method, firstly, we add a constraint by a virtual poten...
Bayesian principal component analysis (BPCA), a probabilistic reformulation of PCA with Bayesian model selection, is a systematic approach to determining the number of essential p...
Finite state machine-based abstractions of software behaviour are popular because they can be used as the basis for a wide range of (semi-) automated verification and validation ...