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Gym Retro: Difference between revisions
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Between April 5th and June 5th of 2018, OpenAI held a contest using the Sonic The Hedgehog™ series of games for SEGA Genesis to have participants create "the best agent for playing custom levels of the Sonic games — without having access to those levels during development." <ref name="”6”"> OpenAI (2018). OpenAI Retro Contest. Retro Contest. https://contest.openai.com/2018-1/</ref> It was a way of measuring the ability of an RL algorithm to generalize based on previous experience. This contest used Gym Retro, providing a test for algorithms on previously unseen video game levels. <ref name="”4”"></ref> | Between April 5th and June 5th of 2018, OpenAI held a contest using the Sonic The Hedgehog™ series of games for SEGA Genesis to have participants create "the best agent for playing custom levels of the Sonic games — without having access to those levels during development." <ref name="”6”"> OpenAI (2018). OpenAI Retro Contest. Retro Contest. https://contest.openai.com/2018-1/</ref> It was a way of measuring the ability of an RL algorithm to generalize based on previous experience. This contest used Gym Retro, providing a test for algorithms on previously unseen video game levels. <ref name="”4”"></ref> | ||
The Retro Contest gave the participants a training set of levels from the Sonic The Hedgehog™ series and OpenAI evaluated the submissions on a test set of custom levels created for the contest. <ref name="”4”"></ref> | The Retro Contest gave the participants a training set of levels from the Sonic The Hedgehog™ series and OpenAI evaluated the submissions on a [[test set]] of custom levels created for the contest. <ref name="”4”"></ref> | ||
OpenAI provided an overview of the contest where participants had to 1) train or script the agent to play Sonic; 2) submit the agent as a Docker container; and then agents received their 3) evaluation on a set of secret test levels; and 5) the agent's score appeared on the leaderboard. <ref name="”6”"></ref> | OpenAI provided an overview of the contest where participants had to 1) train or script the agent to play Sonic; 2) submit the agent as a Docker container; and then agents received their 3) evaluation on a set of secret test levels; and 5) the agent's score appeared on the leaderboard. <ref name="”6”"></ref> | ||