Arena

Reinforcement learning streamlined with the platform built for RLOps

Trusted by leading institutions

MIT CSAIL logo

Arena has significantly streamlined our RL development workflow, making training and deploying agents a breeze. The platform's hyperparameter tuning capabilities have dramatically accelerated our experimentation and improved the performance of our models.

Andrew Nestor
T&I Team, Decision Lab

Arena pricing

The resources you need to succeed.

Free

For students, researchers, and developers exploring reinforcement learning

110 training credits
(~20 hours)

$0

Get started
1 workspace user
Optimised compute resources
1 GB storage
1 active deployment
Community support

Professional

For small teams and individual professionals building production RL systems

500 training credits per month
(~90 hours)

$600/ month

Subscribe
Up to 5 workspace users
Optimised compute resources
50 GB storage
5 active deployments
Priority support - 24 hour SLA
Most popular

Business

For growing teams and organisations with building and deploying large RL workloads

2000 training credits per month
(~360 hours)

$1800/ month

Subscribe
Up to 20 workspace users
Optimised compute resources
250 GB storage
20 active deployments
Priority support - 8 hour SLA

Enterprise

For large organisations deploying mission-critical RL applications with custom requirements

Uncapped training credits

Tailored pricing

Get in touch
Unlimited workspace users
Optimised compute resources
Uncapped storage
Uncapped deployments
Custom support SLAs

Running low on training credits?

Add credits in seconds. No plan upgrades necessary.

Get credits

Free

For students, researchers, and developers exploring reinforcement learning

110 training credits
(~20 hours)

$0

Get started
1 workspace user
Optimised compute resources
1 GB storage
1 active deployment
Community support

Professional

For small teams and individual professionals building production RL systems

500 training credits per month
(~90 hours)

$600/ month

Subscribe
Up to 5 workspace users
Optimised compute resources
50 GB storage
5 active deployments
Priority support - 24 hour SLA
Most popular

Business

For growing teams and organisations with building and deploying large RL workloads

2000 training credits per month
(~360 hours)

$1800/ month

Subscribe
Up to 20 workspace users
Optimised compute resources
250 GB storage
20 active deployments
Priority support - 8 hour SLA

Enterprise

For large organisations deploying mission-critical RL applications with custom requirements

Uncapped training credits

Tailored pricing

Get in touch
Unlimited workspace users
Optimised compute resources
Uncapped storage
Uncapped deployments
Custom support SLAs

Running low on training credits?

Add credits in seconds. No plan upgrades necessary.

Get credits

> import agilerl

open-source v2 released. 10x faster training.

Single-agent and Multi-agent Support

Train on-policy, off-policy, offline, multi-agent and contextual multi-armed bandits with unmatched speed and performance

Evolutionary Hyperparameter Optimization

Achieve automatic, optimal performance in a single training run through hyperparameter and neural network evolution

Distributed Training

Take full advantage of your entire compute stack for online and offline reinforcement learning with multi-GPU support

Hierarchical Skills

Solve complex problems by breaking down tasks into smaller, learnable sub-tasks with the AgileRL Skills wrapper

Community Driven

Benefit from the contributions of top research labs and institutions, shaped by academic citations and 220,000+ downloads

Case studies

Discover how AgileRL is delivering value

See all

Optimising Logistics Efficiency

Dramatically increasing utilisation and reducing training time for complex bin-packing with Decision Lab

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Revolutionising Algorithmic Trading

Maximising returns from high-frequency trading using reinforcement learning agents with Maxvankekeren-IT

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Advancing Robot Learning

Pushing the boundaries of multi-agent reinforcement learning with University of Minnesota

Read the case study