Task Transfer by Preference-Based Cost Learning

The goal of task transfer in reinforcement learning is migrating the action policy of an agent to the target task from the source task. Given their successes on robotic action planning, current methods mostly rely on two requirements: exactly-relevant expert demonstrations or the explicitly-coded cost function on target task, both of which, however, are inconvenient to obtain in practice. In this paper, we relax these two strong conditions by developing a novel task transfer framework where the expert preference is applied as a guidance. In particular, we alternate the following two steps: Firstly, letting experts apply pre-defined preference rules to select related expert demonstrates for the target task. Secondly, based on the selection result, we learn the target cost function and trajectory distribution simultaneously via enhanced Adversarial MaxEnt IRL and generate more trajectories by the learned target distribution for the next preference selection. The theoretical analysis on the distribution learning and convergence of the proposed algorithm are provided. Extensive simulations on several benchmarks have been conducted for further verifying the effectiveness of the proposed method.Comment: Accepted to AAAI 2019. Mingxuan Jing and Xiaojian Ma contributed equally to this wor

Some Fixed Point Results for the Generalized FF-suzuki Type Contractions in bb-metric Spaces

Compared with the previous work, the aim of  this paper is to introduce the more general concept of the generalized $F$-Suzuki type contraction mappings in $b$-metric spaces, and to establish some fixed point theorems in the setting of $b$-metric spaces. Our main results unify, complement and generalize the previous works in the existing literature

Pulmonary alveolar type I cell population consists of two distinct subtypes that differ in cell fate.

Pulmonary alveolar type I (AT1) cells cover more than 95% of alveolar surface and are essential for the air-blood barrier function of lungs. AT1 cells have been shown to retain developmental plasticity during alveolar regeneration. However, the development and heterogeneity of AT1 cells remain largely unknown. Here, we conducted a single-cell RNA-seq analysis to characterize postnatal AT1 cell development and identified insulin-like growth factor-binding protein 2 (Igfbp2) as a genetic marker specifically expressed in postnatal AT1 cells. The portion of AT1 cells expressing Igfbp2 increases during alveologenesis and in post pneumonectomy (PNX) newly formed alveoli. We found that the adult AT1 cell population contains both Hopx+Igfbp2+ and Hopx+Igfbp2- AT1 cells, which have distinct cell fates during alveolar regeneration. Using an Igfbp2-CreER mouse model, we demonstrate that Hopx+Igfbp2+ AT1 cells represent terminally differentiated AT1 cells that are not able to transdifferentiate into AT2 cells during post-PNX alveolar regeneration. Our study provides tools and insights that will guide future investigations into the molecular and cellular mechanism or mechanisms underlying AT1 cell fate during lung development and regeneration

From IT Capabilities to Supply Chain Performance: The Mediating Effects of Supply Chain Agility and Absorptive Capacity

While information technologies have been taken as the competitive tool in improving supply chain performance, its investment cannot guarantee to meet firms’ performance expectations. Our understanding about the mechanisms by which IT affects supply chain performance remains unclear. Based on the perspective of dynamic capabilities theory, we derive a model to examine the effects of a firm’s IT capabilities, namely IT infrastructure flexibility and IT assimilation on supply chain performance. In particular, we examine the mediating effects of the firm’s higher-order organizational capabilities, namely supply chain agility and absorptive capacity on the relationships between IT capabilities and supply chain performance. Results from a survey show that the firm’s supply chain agility can fully mediate IT capabilities’ influence, while absorptive capacity partially mediate the influences of IT capabilities on supply chain agility. In addition, IT infrastructure flexibility can improve the firm’s IT assimilation. Contributions and implications of this study are discussed

High-Speed Low-Power Viterbi Decoder Design for TCM Decoders

High-speed, low-power design of Viterbi decoders for trellis coded modulation (TCM) systems is presented in this paper. It is well known that the Viterbi decoder (VD) is the dominant module determining the overall power consumption of TCM decoders. We propose a pre-computation architecture incorporated with T-algorithm for VD, which can effectively reduce the power consumption without degrading the decoding speed much. A general solution to derive the optimal pre-computation steps is also given in the paper. Implementation result of a VD for a rate-3/4 convolutional code used in a TCM system shows that compared with the full trellis VD, the pre-computation architecture reduces the power consumption by as much as 70% without performance loss, while the degradation in clock speed is negligible.This is the author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by IEEE and can be found at: http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=6257480. ©2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Keywords: Trellis coded modulation (TCM), Viterbi decoder, VLS