WebOct 27, 2024 · When the bird collides set the reward of -1, penalizing the collision. private void OnTriggerEnter2D(Collider2D collision2d) {SetReward(-1f); EndEpisode();} In the reinforcement learning process the agent aims to maximize the reward, i.e. the behavior that leads to higher reward is selected as opposed to that which leads to lower reward. WebKeywords: Reinforcement Learning, Flappy Bird, Machine Learning. 1. Introduction The project the study is doing is that a Flappy Bird Clone using python-pygame. Flappy bird is a

DQN（Deep Q-learning）入门教程（四）之 Q-learning Play …

WebSep 1, 2024 · Reinforcement Learning solution for Flappy Bird with PPO algorithm. The quick summary of my question: I'm trying to solve a clone of the Flappy Bird game found … WebSep 22, 2024 · The agent is provided with rational human-level inputs to guide its learning. Two AI strategies are comparatively evaluated: generic RL and a standard 3 layer NN structure with genetic optimization algorithm (Neuroevolution) to learn playing the Flappy Bird game and improve progressively their performance. Fig. 1. biting worm

Playing Flappy Bird with Two Different Value Learning …

WebMay 4, 2024 · After learning basic knowledge of deep reinforcement learning algorithm, I started to think about implementing something interesting to practice. I have already train … WebThe aim of this work is to create and teach an agent based on Deep Reinforcement Learning, also create an environment which will operate in a similar way to game Flappy Bird. This work has to show that browser is capable of Neural Network computations and can be pretty efficient in reinforcement learning for Flappy Bird. biting women