Psychophysiological mechanisms for learning tasks solving of different complexity

an investigation of accuracy and complexity across different proficiency levels in written narrative task

abstract this quasi-experimental study was aimed at examining the impact of storyline complexity on the grammatical accuracy and complexity of advanced and intermediate efl learners. a total of 65 advanced and intermediate efl learners were selected from iran language institute (ili). an intact group including 35 intermediate participants and another intact group with 30 advanced participants ...

Towards Learning Path Planning for Solving Complex Robot Tasks

For solving complex robot tasks it is necessary to incorpo rate path planning methods that are able to operate within di erent high dimensional con guration spaces containing an unknown number of obstacles Based on Advanced A algorithm AA using expansion matrices instead of a simple expansion logic we propose a further im provement of AA enabling the capability to learn directly from sample pla...

development of different optical methods for determination of glucose using cadmium telluride quantum dots and silver nanoparticles

a simple, rapid and low-cost scanner spectroscopy method for the glucose determination by utilizing glucose oxidase and cdte/tga quantum dots as chromoionophore has been described. the detection was based on the combination of the glucose enzymatic reaction and the quenching effect of h2o2 on the cdte quantum dots (qds) photoluminescence.in this study glucose was determined by utilizing glucose...

Learning Grammars for Different Parsing Tasks by Partition Search

Learning by Playing - Solving Sparse Reward Tasks from Scratch

We propose Scheduled Auxiliary Control (SACX), a new learning paradigm in the context of Reinforcement Learning (RL). SAC-X enables learning of complex behaviors – from scratch – in the presence of multiple sparse reward signals. To this end, the agent is equipped with a set of general auxiliary tasks, that it attempts to learn simultaneously via off-policy RL. The key idea behind our method is...