<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>Herself's Artificial Intelligence &#187; game ai</title>
	<atom:link href="http://herselfsai.com/category/game-ai/feed" rel="self" type="application/rss+xml" />
	<link>http://herselfsai.com</link>
	<description>Humans, meet your replacements.</description>
	<lastBuildDate>Wed, 21 Mar 2012 14:26:27 +0000</lastBuildDate>
	<language>en</language>
	<sy:updatePeriod>hourly</sy:updatePeriod>
	<sy:updateFrequency>1</sy:updateFrequency>
	<generator>http://wordpress.org/?v=3.3.2</generator>
		<item>
		<title>Simple artificial life program source code</title>
		<link>http://herselfsai.com/2008/02/evolving-bugs.html</link>
		<comments>http://herselfsai.com/2008/02/evolving-bugs.html#comments</comments>
		<pubDate>Wed, 27 Feb 2008 11:00:46 +0000</pubDate>
		<dc:creator>Linda MacPhee-Cobb</dc:creator>
				<category><![CDATA[game ai]]></category>
		<category><![CDATA[source code]]></category>

		<guid isPermaLink="false">http://timestocome.org/herselfsai/2008/02/evolving-bugs.html</guid>
		<description><![CDATA[I am finishing up my reading of &#8216;The Magic Machine: A Handbook of Computer Sorcery&#8216; and there were only two programs left to write. I thought I&#8217;d wipe the first one out in a day. Heh, it took three. In a chapter of the book the author discusses early attempts at genetically evolving artificial life. [...]]]></description>
		<wfw:commentRss>http://herselfsai.com/2008/02/evolving-bugs.html/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Neural network levels playing field in MMORGs</title>
		<link>http://herselfsai.com/2007/11/neural-network-levels-playing-field-in-mmogs.html</link>
		<comments>http://herselfsai.com/2007/11/neural-network-levels-playing-field-in-mmogs.html#comments</comments>
		<pubDate>Mon, 19 Nov 2007 11:00:50 +0000</pubDate>
		<dc:creator>Linda MacPhee-Cobb</dc:creator>
				<category><![CDATA[artificial intelligence in the news]]></category>
		<category><![CDATA[game ai]]></category>
		<category><![CDATA[human replacement]]></category>

		<guid isPermaLink="false">http://timestocome.org/herselfsai/2007/11/neural-network-levels-playing-field-in-mmogs.html</guid>
		<description><![CDATA[All these recent studies using neural networks to predict human behavior have found a purpose. They are being trained and used on game users computers to get around network lag in games by predicting the gamers next move. Lag time is the ping time between you and the game computer. If two players are shooting [...]]]></description>
		<wfw:commentRss>http://herselfsai.com/2007/11/neural-network-levels-playing-field-in-mmogs.html/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Gamasutra article on Turning Algorithms for Strategy Games</title>
		<link>http://herselfsai.com/2007/08/gamasutra-article-on-turning-algorithms-for-strategy-games.html</link>
		<comments>http://herselfsai.com/2007/08/gamasutra-article-on-turning-algorithms-for-strategy-games.html#comments</comments>
		<pubDate>Fri, 17 Aug 2007 12:00:00 +0000</pubDate>
		<dc:creator>Linda MacPhee-Cobb</dc:creator>
				<category><![CDATA[game ai]]></category>
		<category><![CDATA[useful websites]]></category>
		<category><![CDATA[human replacement]]></category>

		<guid isPermaLink="false">http://timestocome.org/herselfsai/2007/08/gamasutra-article-on-turning-algorithms-for-strategy-games.html</guid>
		<description><![CDATA[Designing AI Algorithms for Turn-Based Strategy Games In action games the AI opponent always has the natural advantage: perfect accuracy and lightning fast reflexes, so the challenge in designing the AI for those games is making it act more human and to be beatable. In turn-based strategy games the tables are turned. Speed and accuracy [...]]]></description>
		<wfw:commentRss>http://herselfsai.com/2007/08/gamasutra-article-on-turning-algorithms-for-strategy-games.html/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Predator Prey Chases using Potential Functions</title>
		<link>http://herselfsai.com/2007/08/predator-prey-chases-using-potential-functions.html</link>
		<comments>http://herselfsai.com/2007/08/predator-prey-chases-using-potential-functions.html#comments</comments>
		<pubDate>Mon, 13 Aug 2007 12:00:00 +0000</pubDate>
		<dc:creator>Linda MacPhee-Cobb</dc:creator>
				<category><![CDATA[game ai]]></category>
		<category><![CDATA[topics in artificial intelligence]]></category>
		<category><![CDATA[things you should know]]></category>

		<guid isPermaLink="false">http://timestocome.org/herselfsai/2007/08/predator-prey-chases-using-potential-functions.html</guid>
		<description><![CDATA[Using potential functions for predator prey movement gives a more realistic chase than using line of sight or other line algorithms. Potential functions are well known in physics and describe attraction and repulsion due to electricity, gravity etc. Potential_Energy = &#8211; Attraction/distance^j + Repulsion/distance^k A strong attraction will cause the predator to chase the prey, [...]]]></description>
		<wfw:commentRss>http://herselfsai.com/2007/08/predator-prey-chases-using-potential-functions.html/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Artificial intelligence solves checkers</title>
		<link>http://herselfsai.com/2007/08/artificial-intelligence-solves-checkers.html</link>
		<comments>http://herselfsai.com/2007/08/artificial-intelligence-solves-checkers.html#comments</comments>
		<pubDate>Fri, 03 Aug 2007 12:00:00 +0000</pubDate>
		<dc:creator>Linda MacPhee-Cobb</dc:creator>
				<category><![CDATA[artificial intelligence in the news]]></category>
		<category><![CDATA[game ai]]></category>
		<category><![CDATA[human replacement]]></category>

		<guid isPermaLink="false">http://timestocome.org/herselfsai/2007/08/artificial-intelligence-solves-checkers.html</guid>
		<description><![CDATA[The game of checkers has roughly 500 billion billion possible positions (5 x 1020). The task of solving the game, determining the final result in a game with no mistakes made by either player, is daunting. Since 1989, almost continuously, dozens of computers have been working on solving checkers, applying state-of-the-art artificial intelligence techniques to [...]]]></description>
		<wfw:commentRss>http://herselfsai.com/2007/08/artificial-intelligence-solves-checkers.html/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
	</channel>
</rss>

