Poke-Env

1
0 Reviews
499
91.35%
Poke-Env is an open-source Python framework that provides an interactive Pokémon battle environment, baseline agent implementations, and utilities to develop, train, and evaluate AI agents on Pokémon Showdown. It supports synchronous and asynchronous battle simulations, integrates with popular reinforcement learning libraries, and offers event-driven callbacks for custom policies. Researchers and developers can easily benchmark strategies, monitor performance metrics, and deploy agents for competitive matchups.
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May 18 2025
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Poke-Env

Poke-Env

0
1
499
Poke-Env
Poke-Env is an open-source Python framework that provides an interactive Pokémon battle environment, baseline agent implementations, and utilities to develop, train, and evaluate AI agents on Pokémon Showdown. It supports synchronous and asynchronous battle simulations, integrates with popular reinforcement learning libraries, and offers event-driven callbacks for custom policies. Researchers and developers can easily benchmark strategies, monitor performance metrics, and deploy agents for competitive matchups.
Added on:
Social & Email:
Platform:
May 18 2025
--
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What is Poke-Env?

Poke-Env is designed to streamline the creation and evaluation of AI agents for Pokémon Showdown battles by providing a comprehensive Python interface. It handles communication with the Pokémon Showdown server, parses game state data, and manages turn-by-turn actions through an event-driven architecture. Users can extend base player classes to implement custom strategies using reinforcement learning or heuristic algorithms. The framework offers built-in support for battle simulations, parallelized matchups, and detailed logging of actions, rewards, and outcomes for reproducible research. By abstracting low-level networking and parsing tasks, Poke-Env allows AI researchers and developers to focus on algorithm design, performance tuning, and comparative benchmarking of battle strategies.

Who will use Poke-Env?

  • AI researchers
  • Reinforcement learning developers
  • Game AI enthusiasts
  • Educators and students in AI

How to use the Poke-Env?

  • Step1: Install poke-env via pip: pip install poke-env
  • Step2: Configure Showdown credentials or set up a local server
  • Step3: Import Poke-Env classes and define a custom player inheriting from BasePlayer
  • Step4: Implement choose_move and event handlers or integrate your RL model
  • Step5: Run battles or a tournament loop and collect performance metrics
  • Step6: Analyze logs and refine strategies based on results

Platform

  • mac
  • windows
  • linux

Poke-Env's Core Features & Benefits

The Core Features

  • Python API for Pokémon Showdown integration
  • Interactive battle environment with synchronous and asynchronous simulations
  • Prebuilt baseline agent implementations
  • Event-driven architecture for custom policy callbacks
  • Integration with reinforcement learning libraries
  • Battle logging and performance analytics

The Benefits

  • Accelerates AI agent development for Pokémon battles
  • Standardized benchmarking and reproducibility
  • Abstracts networking and parsing complexities
  • Easily extensible for custom strategies
  • Enables parallelized simulations for faster training

Poke-Env's Main Use Cases & Applications

  • Reinforcement learning research on turn-based battles
  • Benchmarking AI strategies in Pokémon Showdown
  • Educational tutorials on game AI development
  • AI competitions and tournaments for Pokémon agents

FAQs of Poke-Env

Poke-Env Company Information

Analytic of Poke-Env

Visit Over Time

Monthly Visits
499
Avg Visit Duration
00:00:00
Page Per Visit
1.02
Bounce Rate
83.11%
Nov 2025 - Jan 2026 All Traffic

Geography

Top 2 Regions
United States
91.35%
Italy
8.65%
Nov 2025 - Jan 2026 Worldwide Desktop Only

Traffic Sources

Direct
45.13%
Search
34.84%
Referrals
11.56%
Social
7.55%
Paid Referrals
0.88%
Mail
0.04%
Nov 2025 - Jan 2026 Desktop Only

Poke-Env Reviews

5/5
Do You Recommend Poke-Env? Leave a Comment Below!

Poke-Env's Main Competitors and alternatives?

  • OpenAI Gym
  • PettingZoo
  • RLlib
  • Gymnasium
  • Stable Baselines3

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