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)
This paper introduces an approach to Reinforcement Learning Algorithm by introducing reduct concept of rough set methodology using a variation of Q-Learning algorithm. Unlike the conventional Q-Learning, the proposed algorithm calculates the reduct from look up table of previous episodes. In modified algorithm first action selection of an agent will based(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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