nowadays, outsourcing is viewed as a trade strategy and organizations tend to adopt new strategies to achieve competitive advantages in the current world of business. focusing on main copmpetencies, and transferring most of activities to outside resources of organization( outsourcing) is one such strategy is. in this paper, we aim to decide on decision maker agent of transportation system, by a...

in this paper a new method based on strut-and-tie model (stm) is proposed to determine the shear capacity of simply supported rc deep beams and an efficiency factor for concrete with considering the effect of web reinforcements. it is assumed that, the total carried shear force by rc deep beam provided by two independent resistance, namely diagonal concrete strut due to strut-and-tie mechanism ...

in this research, al-ni particle composite strips are formed by accumulative roll bonding (arb) process using al strips and ni powder. the rule of arb cycles and volume percentage (vol%) of ni powder on the microstructure, wear resistance and mechanical properties of the formed composites are investigated. according to the tensile test results, the yield stress and tensile strengths of the al -...

In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...

OBJECTIVE Neural hypo-sensitivity to cues predicting positive reinforcement has been observed in ADHD using the Monetary Incentive Delay (MID) task. Here we report the first study using an electrophysiological analogue of this task to distinguish between (i) cue related anticipation of reinforcement and downstream effects on (ii) target engagement and (iii) performance in a clinical sample of a...

The reinforcement learning problem is a very difficult problem when considering real-size applications. To solve it, we think that many issues should be studied altogether. To achieve such an endeavor, we also think that it is quite common that human begins can provide help on-the-fly to the reinforcement learner, that is when he/she sees how the learner is (mis)behaving, or could perform bette...

Reinforcement schedules are considered in relation to applied behavior analysis by examining several recent laboratory experiments with humans and other animals. The experiments are drawn from three areas of contemporary schedule research: behavioral history effects on schedule performance, the role of instructions in schedule performance of humans, and dynamic schedules of reinforcement. All o...

This report surveys recent development on the global combinatorial optimization using reinforcement learning methods. It introduces the general background of combinatorial optimization problems and reinforcement learning techniques, describes observations and previous works in this area, and focuses on Boyan and Moore's recent work, the STAGE algorithm with the assistant of reinforcement learning.