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This paper describes InfoGAN, an information-theoretic extension to the Gener-ative Adversarial Network that is able to learn disentangled representations in a completely unsupervised manner. InfoGAN is a generative adversarial network that also maximizes the mutual information between a small subset of the latent variables and the observation. We derive a(More)
Recently, researchers have made significant progress combining the advances in deep learning for learning feature representations with reinforcement learning. Some notable examples include training agents to play Atari games based on raw pixel data and to acquire advanced manipulation skills using raw sensory inputs. However , it has been difficult to(More)
Scalable and effective exploration remains a key challenge in reinforcement learning (RL). While there are methods with optimality guarantees in the setting of discrete state and action spaces, these methods cannot be applied in high-dimensional deep RL scenarios. As such, most contemporary RL relies on simple heuristics such as-greedy exploration or adding(More)
4 OpenAI ABSTRACT Count-based exploration algorithms are known to perform near-optimally when used in conjunction with tabular reinforcement learning (RL) methods for solving small discrete Markov decision processes (MDPs). It is generally thought that count-based methods cannot be applied in high-dimensional state spaces, since most states will only occur(More)
Security is not taken into account by default in the Representational State Transfer (REST) architecture, but its layered architecture provides many opportunities for implementing it. In this paper, a security mechanism for Web Service communication through mobile clients devices is proposed, that conforms to the REST architecture as much as possible. This(More)
INTRODUCTION The length of stay of critically ill patients in the intensive care unit (ICU) is an indication of patient ICU resource usage and varies considerably. Planning of postoperative ICU admissions is important as ICUs often have no nonoccupied beds available. PROBLEM STATEMENT Estimation of the ICU bed availability for the next coming days is(More)
Although geometric routing is proposed as a memory-efficient alternative to traditional lookup-based routing and forwarding algorithms, it still lacks: (i) adequate mechanisms to trade stretch against load balancing, and (ii) robustness to cope with network topology change. The main contribution of this paper involves the proposal of a family of routing(More)
Geometric routing has been proposed in literature as a memory-efficient alternative to traditional lookup-based routing and forwarding algorithms. However, existing geometric routing schemes lack the ability to address network link and node failures in a natural way, while maintaining a low path stretch. The main contribution of this paper is a novel(More)