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This paper introduces application of Multi Agent Deep Deterministic Policy Gradients algorithm for multiple traffic intersection problems. The problem of decrease in waiting time at traffic intersections is still unsolved. Reinforcement learning is the recent technique which was introduced in past years. This paper is an attempt to apply Reinforcement Learning for multiple intersections.

With the propulsion of technological innovation and advances, data today is being compared to oil of the previous century. Today, our world is overwhelmed by the gathering and dissemination of huge amounts of data. Thus, Text Summarization has become a valuable tool which would help us save time and efforts. Text summarization can be defined as the process of presenting the most important information from a source (or a set of sources) to produce a concise version for a particular user and tasks, without causing any significant loss of information. In this paper, various text summarization techniques- both extractive and abstractive have been surveyed and presented.