Learning to Perceive and Act by Trial and Error

This article considers adaptive control architectures that integrate active sensory-motor systems with decision systems based on reinforcement learning. One unavoidable consequence of active perception is that the agent's internal representation often confounds external world states. We call this phoenomenon perceptual aliasingand show that it destabilizes existing reinforcement learning algorithms with respect to the optimal decision policy. We then describe a new decision system that overcomes these difficulties for a restricted class of decision problems. The system incorporates a perceptual subcycle within the overall decision cycle and uses a modified learning algorithm to suppress the effects of perceptual aliasing. The result is a control architecture that learns not only how to solve a task but also where to focus its visual attention in order to collect necessary sensory information.     

In situ formation of multi scale reinforcing phases to improve performance of Al2O3-SiC C castables

In order to improve the physical properties and slag corrosion resistance of refractory materials for hot metal pretreatment, different contents of composite metal powders (CMP) were introduced into Al2O3-SiC-C refractory castables. The effect of CMP on the microstructure, physical properties and slag corrosion resistance of Al2O3-SiC-C refractory castables were studied. The results show that the multi scale reinforcing phases including flake crystals, rod shaped fibers, filamentous fibers and whiskers are in situ formed in the samples with addition of CMP, which result to the improvement of the cold modulus of rupture and cold crushing strength. When the addition of CMP is 6 wt.%, the high temperature modulus of rupture increases by 231%, the thermal shock resistance increases by 77% after thermal shock by water cooling 5 times and the percentage of the slag resistant area reduces by 37.2%.     

On the learning control of a robot manipulator

This paper derives a learning control law to achieve trajectory following for a robot manipulator. The controller consists of two parts, a computed torque servo for the rigid body terms that can be modelled and a learning law for the unmodelled dynamics. An advantage of this method is that bounds can be assigned to the position and velocity tracking errors.     

Learning to Predict Non-Deterministically Generated Strings

In this article we present an algorithm that learns to predict non-deterministically generated strings. The problem of learning to predict non-deterministically generated strings was raised by Dietterich and Michalski (1986). While their objective was to give heuristic techniques that could be used to rapidly and effectively learn to predict a somewhat limited class of strings, our objective is to give an algorithm which, though impractical, is capable of learning to predict a very general class. Our algorithm is meant to provide a general framework within which heuristic techniques can be effectively employed.     

Extending boosting for large scale spoken language understanding

We propose three methods for extending the Boosting family of classifiers motivated by the real-life problems we have encountered. First, we propose a semisupervised learning method for exploiting the unlabeled data in Boosting. We then present a novel classification model adaptation method. The goal of adaptation is optimizing an existing model for a new target application, which is similar to the previous one but may have different classes or class distributions. Finally, we present an efficient and effective cost-sensitive classification method that extends Boosting to allow for weighted classes. We evaluated these methods for call classification in the AT&;T VoiceTone^® spoken language understanding system. Our results indicate that it is possible to obtain the same classification performance by using 30% less labeled data when the unlabeled data is utilized through semisupervised learning. Using model adaptation we can achieve the same classification accuracy using less than half of the labeled data from the new application. Finally, we present significant improvements in the “important” (i.e., higher weighted) classes without a significant loss in overall performance using the proposed cost-sensitive classification method.     

Age of acquisition: Its neural and computational mechanisms.

The acquisition of new skills over a life span is a remarkable human ability. This ability, however, is constrained by age of acquisition (AoA); that is, the age at which learning occurs significantly affects the outcome. This is most clearly reflected in domains such as language, music, and athletics. This article provides a perspective on the neural and computational mechanisms underlying AoA in language acquisition. The authors show how AoA modulates both monolingual lexical processing and bilingual language acquisition. They consider the conditions under which syntactic processing and semantic processing may be differentially sensitive to AoA effects in second-language acquisition. The authors conclude that AoA effects are pervasive and that the neural and computational mechanisms underlying learning and sensorimotor integration provide a general account of these effects. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

植筋施工工艺

以某网球馆改造工程为例 ,就植筋技术的概念及所用材料进行了介绍 ,详细阐述了其施工工艺流程及措施 ,指出植筋技术具有工艺简单、操作方便、造价相对较低等优点     

简析Ⅲ类PHC管桩的成因及加固补强处理方法

本文主要通过Ⅲ类PHC管桩的形成分析,经过各方论证采用了合适的处理方法,取得了较好的效果。     

David W. Johnson: Award for Distinguished Contributions of Applications of Psychology to Education and Training.

Provides the biography of David W. Johnson and announces that he has won the Award for Distinguished Contributions of Applications of Psychology to Education and Training for programmatic research, comprehensive research reviews, and revision of theory over four decades of persistence that have provided the knowledge foundation for cooperative learning, constructive controversy, conflict resolution, and peer mediation training. A selected bibliography is also provided. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Choice With Initial and Terminal Link Reinforcement: An Alternative Self-Control Paradigm.

Self-control is demonstrated when a less desirable immediate outcome is chosen to ensure a substantially better future. In a novel animal analogue of this situation, primary reinforcement was delivered in both the initial and terminal links of a concurrent chain schedule. Rats made initial link choices between equal amounts of ethanol-free or ethanol-containing milk. Choosing the ethanol-free reinforcer resulted in delivery of the larger terminal link reinforcer and was thus analogous to self-control. Self-control decreased as the delay between initial and terminal links increased. The results have implications for human choice situations where decisions are made between two immediately available reinforcement alternatives each associated with a different delayed outcome. (PsycINFO Database Record (c) 2010 APA, all rights reserved)