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<!DOCTYPE html>
<html class="no-js" lang="en" dir="ltr">
<head>
<title>{{ page.title }}</title>
<meta charset="UTF-8">
<meta name="description" content="AI Robotics Project" />
<meta name="keywords" content="AI, Robotics, MIT, Manipal">
<meta name="author" content="Shrijit Singh">
<meta name="powered-by" content="Dheeraj Mohan">
<meta name="design" content="Sarathkrishnan Ramesh">
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<h4>Decoding bits for you</h4>
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<h3 class="title">Navigating with grid-like representations in artificial agents</h3>
<span class="author">Shivesh Khaitan</span><span class="date">August 4, 2018</span>
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Most animals, including humans, are able to flexibly navigate the world they live in – exploring new areas, returning quickly to remembered places, and taking shortcuts. Indeed, these abilities feel so easy and natural that it is not immediately obvious how complex the underlying processes really are. In contrast, spatial navigation remains a substantial challenge for artificial agents whose abilities are far outstripped by those of mammals.
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buzz =["Cryptography", "AritificialIntelligence", "Robotics", "Blockchain", "DeepMind", "NeuralNetwork", "BackPropogation", "Convolution", "Tensorflow"]
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