— We present a new motion planning framework that explicitly considers uncertainty in robot motion to maximize the probability of avoiding collisions and successfully reaching a ...
Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
straction and explained how the Representational State Transfer (REST) architectural style is one alternative that can yield a superior approach to building distributed systems. Be...
Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...
Effect axioms constitute the cornerstone of formal theories of action in AI. They drive standard reasoning tasks, especially prediction. These tasks need not be coupled with actual...