poke hack

Inspiration

The inspiration for Poke Hack came from the desire to build a smarter, more strategic Pokémon bot capable of making better decisions during battle. We wanted to incorporate game mechanics like weather conditions, type effectiveness, and move setups into the decision-making process to create a more competitive bot.

What it does

Poke Hack is a Pokémon battle bot that uses advanced logic to determine optimal moves and switches during a battle. The bot evaluates factors like type effectiveness, the weather (e.g., sandstorm), stat boosts, and opponent abilities to make strategic decisions. It can perform advanced move setups such as Swords Dance under favorable conditions and switch Pokémon when necessary to maintain battle control.

How we built it

We built Poke Hack using the poke-env Python library, which simulates Pokémon Showdown battles. The bot's decision-making logic was carefully programmed to account for various in-game conditions such as weather effects, opponent types, and move priority. We also integrated type-checking mechanisms and stat-boost strategies to improve its performance.

Challenges we ran into

One of the main challenges we faced was implementing logic that could handle complex battle scenarios, such as dynamically switching Pokémon based on both the current weather and the opponent's team composition. Additionally, ensuring that the bot could properly evaluate type effectiveness and avoid string comparisons (since Pokémon types are represented as enums) required careful coding and debugging.

Accomplishments that we're proud of

We're proud of successfully creating a bot that can dynamically adapt its strategy based on in-game conditions. The bot's ability to use advanced move setups like Belly Drum for Azumarill or Swords Dance for Excadrill under sandstorm conditions makes it a formidable opponent. Additionally, we overcame several technical challenges related to managing game states and optimizing move selection.

What we learned

Throughout the project, we gained a deeper understanding of how the Pokémon battle mechanics work at a programmatic level. We also learned how to efficiently manage a complex decision-making process in real-time using Python, incorporating the strengths of enums, condition checks, and modular logic to improve the bot’s performance.

What's next for Poke Hack

In the future, we plan to enhance Poke Hack by integrating machine learning models to further refine its decision-making process. We also aim to support more advanced strategies, such as predicting the opponent’s moves, using hazard control, and improving team synergy. Additionally, we’ll expand the bot’s capabilities to handle more diverse battle formats and complex weather conditions.

Built With

• python