<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Game Theory on English AI Terms Dictionary</title><link>https://terms-en.ai-term-hub.com/en/tags/game-theory/</link><description>Recent content in Game Theory on English AI Terms Dictionary</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 18 Jul 2026 11:44:44 +0000</lastBuildDate><atom:link href="https://terms-en.ai-term-hub.com/en/tags/game-theory/index.xml" rel="self" type="application/rss+xml"/><item><title>Zeuthen Strategy</title><link>https://terms-en.ai-term-hub.com/en/terms/zeuthen_strategy/</link><pubDate>Sat, 18 Jul 2026 10:20:18 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/zeuthen_strategy/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>The Zeuthen strategy is a rule-based approach for bargaining in multi-agent negotiations. It calculates the maximum risk an agent is willing to take to push for its preferred outcome, defined as the ratio of utility loss if agreement fails versus utility gain if the opponent concedes. Agents using this strategy will concede only when their calculated risk exceeds that of their counterpart, ensuring efficient convergence to Pareto-optimal agreements in cooperative settings.&lt;/p></description></item><item><title>Nash</title><link>https://terms-en.ai-term-hub.com/en/terms/nash/</link><pubDate>Sat, 18 Jul 2026 09:34:16 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/nash/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>In AI, particularly in Multi-Agent Systems and Reinforcement Learning, Nash Equilibrium describes a stable state where each agent&amp;rsquo;s strategy is optimal given the strategies of all other agents. No single agent has an incentive to deviate unilaterally. This concept is crucial for training adversarial networks, designing autonomous vehicle negotiation protocols, and developing algorithms that converge to stable outcomes in competitive environments. It provides a theoretical foundation for understanding strategic interactions among rational AI agents.&lt;/p></description></item></channel></rss>