Deepshikha Pandey

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This paper introduces an approach to Q-learning algorithm with rough set theory introduced by Zdzislaw Pawlak in 1981. During Q-learning, an agent makes action selections in an effort to maximize a reward signal obtained from the environment. Based on reward, agent will make changes in its policy for future actions. The problem considered in this paper is(More)
— This paper introduces an approach to Reinforcement Learning Algorithm by comparing their immediate rewards using a variation of Q-Learning algorithm. Unlike the conventional Q-Learning, the proposed algorithm compares current reward with immediate reward of past move and work accordingly. Relative reward based Q-learning is an approach towards interactive(More)
Angiogenesis is a promising area of research that targets key therapeutic areas like cancer; wound healing, inflammatory diseases, etc. There is an increasing demand for screening of potential angiogenic and anti-angiogenic agents using sensitive, robust cell-based assays. We have developed a reporter vector containing cis-acting elements that respond to(More)
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