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2048

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Python Programming Learning Circle
Python Programming Learning Circle
Apr 15, 2025 · Game Development

Python Game Development Examples: 2048, Snake, Tetris, and LianLianKan with Source Code

This article introduces four classic games—2048, Snake, Tetris, and LianLianKan—explaining their design principles, gameplay mechanics, and providing complete Python source code using Pygame and Tkinter, suitable for learners with basic Python and game programming knowledge.

2048Game developmentLianLianKan
0 likes · 33 min read
Python Game Development Examples: 2048, Snake, Tetris, and LianLianKan with Source Code
Python Programming Learning Circle
Python Programming Learning Circle
Feb 19, 2024 · Game Development

Python Pygame Implementations of Classic Games: 2048, Snake, Tetris, and LianLianKan

This article provides step-by-step tutorials and complete Python Pygame source code for implementing four classic games—2048, Snake, Tetris, and LianLianKan—explaining game mechanics, design principles, and code structure to help Python developers build and understand these interactive applications.

2048Game developmentLianLianKan
0 likes · 43 min read
Python Pygame Implementations of Classic Games: 2048, Snake, Tetris, and LianLianKan
Python Programming Learning Circle
Python Programming Learning Circle
Nov 13, 2021 · Game Development

Python Game Development Tutorials: 2048, Snake, Tetris, and LianLianKan with Pygame and Tkinter

This article provides step‑by‑step Python tutorials for creating classic games—including 2048, Snake, Tetris, and LianLianKan—detailing design principles, core logic, and complete source code using Pygame and Tkinter for learners with basic Python and game‑programming knowledge.

2048Game developmentLianLianKan
0 likes · 39 min read
Python Game Development Tutorials: 2048, Snake, Tetris, and LianLianKan with Pygame and Tkinter
DataFunTalk
DataFunTalk
Dec 10, 2019 · Artificial Intelligence

Applying Deep Reinforcement Learning (DQN) to the 2048 Game: Experiments and Insights

This article details a series of reinforcement‑learning experiments on the 2048 game, from random baselines through DQN implementations, classical value‑iteration methods, network redesigns, and Monte‑Carlo tree search, highlighting challenges such as reward design, over‑estimation, and exploration while achieving scores up to 34 000 and tiles of 2048.

2048AIDQN
0 likes · 8 min read
Applying Deep Reinforcement Learning (DQN) to the 2048 Game: Experiments and Insights