In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
We present a new algorithm to measure domain-specific readability. It iteratively computes the readability of domainspecific resources based on the difficulty of domain-specific c...
Abstract In future, parallel and distributed computing paradigms will replace nowadays predominant sequential and centralized ones. Facing the challenge to support the construction...
The saddle point framework provides a convenient way to formulate many convex variational problems that occur in computer vision. The framework unifies a broad range of data and re...
Jan Lellmann, Dirk Breitenreicher, Christoph Schn&...
This article is a critical review of computational techniques used to model, analyse and simulate signalling networks. We propose a conceptual framework, and discuss the role of s...