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	<title>uber ai &#8211; EFR Technology Group</title>
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	<title>uber ai &#8211; EFR Technology Group</title>
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		<title>Uber AI plays any Atari 2600 game with &#8216;superhuman&#8217; skill</title>
		<link>https://www.efrtechgroup.com/ai/uber-ai-plays-any-atari-2600-game-with-superhuman-skill/</link>
		
		<dc:creator><![CDATA[Randall]]></dc:creator>
		<pubDate>Thu, 30 Apr 2020 01:28:32 +0000</pubDate>
				<category><![CDATA[Ai]]></category>
		<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[atari]]></category>
		<category><![CDATA[atari 2600]]></category>
		<category><![CDATA[autonomous]]></category>
		<category><![CDATA[Games]]></category>
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		<category><![CDATA[Uber]]></category>
		<category><![CDATA[uber ai]]></category>
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		<category><![CDATA[Video Games]]></category>
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					<description><![CDATA[[ad_1] DeepMind isn’t the only one with an Atari-savvy AI. A team of Uber AI researchers has developed a set of algorithms, Go-Explore, that reportedly beats any Atari 2600 game with “superhuman” scores, including ones where AI previously had trouble besting its organic rivals. The key is a system that takes care to remember promising [&#8230;]]]></description>
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<p>DeepMind isn’t the only one with an <a href="https://www.engadget.com/2020-04-01-deepmind-agent57-ai-atari.html">Atari-savvy AI</a>. A team of Uber AI researchers has <a href="https://twitter.com/jeffclune/status/1255149777332785155" target="_blank" rel="noopener noreferrer">developed</a> a set of algorithms, Go-Explore, that reportedly beats any Atari 2600 game with “superhuman” scores, including ones where AI previously had trouble besting its organic rivals. The key is a system that takes care to remember promising states and returns to those states before it sets out exploring.</p>
<p>Go-Explore saw improvement by “orders of magnitude” in some games. It was the first to beat every level in <em>Montezuma’s Revenge</em>, and got a “near-perfect” <em>Pitfall</em> score — both of these are particularly challenging for reinforcement learning systems like this. DeepMind’s Agent57 reached a similar benchmark, <a href="https://twitter.com/jeffclune/status/1255149782231740419" target="_blank" rel="noopener noreferrer">according</a> to the team’s Jeff Clune, but through “entirely different methods.” That gives developers a “diversity” of approaches to the same tasks.</p>
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<br /><a href="https://www.engadget.com/uber-ai-masters-atari-games-012832222.html">Source link </a></p>
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