Technology 3 min read

OpenAI Unveils Massive Reinforcement Learning Simulator for AI Agents

In a big push towards improving ai agents, Open AI has released a new reinforcement learning platform to study the behaviors and possible improvements that can be added to AI agents.

Image via OpenAI

Image via OpenAI

Yesterday, OpenAI announced its release of a massive multiagent game environment for reinforcement learning agents. The company’s newest Neural MMO platform reportedly supports a “large, variable number of agents” within a “persistent and open-ended task.”

In a statement, OpenAI wrote:

“In recent years, multiagent settings have become an effective platform for deep reinforcement learning research. Despite this progress, there are still two main challenges for multiagent reinforcement learning. We need to create open-ended tasks with a high complexity ceiling: current environments are either complex but too narrow or open-ended but too simple.”

According to OpenAI, more benchmark environments are required to quantify the learning progress of AI agents in large population scales and persistence. Apparently, an MMO structure is the best solution as it simulates a vast ecosystem where a variable number of players can persistently compete within large environments.

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A demo of OpenAI’s Neural MMO reinforcement learning simulation for AI agents | OpenAI

MMO Reinforcement Learning Simulation

OpenAI claims that its Neural MMO reinforcement learning simulator can address the critical challenges of training AI agents. These challenges include persistence, scale, efficiency, and expansion.

The MMO simulator allows players or agents to join available servers or environments containing an auto-generated tile-based game map of configurable size. There are traversable tiles like food-bearing forests and grass tiles along with non-traversable tiles like water and solid stone tiles.

Agents will spawn at random locations along the edges of the environment where they need to gather food and water while avoiding damage from other agents.

OpenAI reported that they trained their AI system to reward agents for staying alive during simulation. The researchers observed that the longer the AI agents communicate with each other, the better they execute tasks.

OpenAi further wrote:

“In the natural world, competition among animals can incentivize them to spread out to avoid conflict. We observe that map coverage increases as the number of concurrent agents increases. Agents learn to explore only because the presence of other agents provides a natural incentive for doing so.”

This is not the first time that OpenAI released an environment for AI agents. Last year, the company released a tool called CoinRun to measure an agent’s ability to transfer its experiences of unfamiliar scenarios.

The Neural MMO reinforcement learning simulation is now available for download on GitHub.

Read More: OpenAI’s Text Generator Could Fuel Future Fake News Fire

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Rechelle Ann Fuertes

Rechelle is an SEO content producer, technical writer, researcher, social media manager, and visual artist. She enjoys traveling and spending time anywhere near the sea with family and friends.

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    Hugh Demson March 05 at 12:05 pm GMT

    Maybe this will finally let me play a game without watching the AI blindly run into walls for half the campaign.

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