Single-player game

Solving JumpIN’ Using Zero-Dependency Reinforcement Learning (Student Abstract)

Reinforcement learning seeks to teach agents to solve problems using numerical rewards as feedback. This makes it possible to incentivize actions that maximize returns despite having no initial strategy or knowledge of their environment. We implement …

Solving JumpIN’ Using Zero-Dependency Reinforcement Learning

Poster presentation in the Student Abstract category on using reinforcement learning to solve JumpIN', a single-player game.

Solving JumpIN' with reinforcement learning

Use Q-learning to solve a single-player game optimally in Python.