ribabot by PlanAi

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  ribabot fight bot2

We embarked on creating Ribabot using reinforcement learning to enhance its intelligence over time. However, the process involved significant trial and error as we navigated through the complexities of reinforcement learning. Our aspiration is to continually upgrade Ribabot to make better decisions and fight more effectively.

Ribabot operates as an AI bot in a fighting game, utilizing reinforcement learning principles to learn and improve its gameplay. It interacts with the game environment by observing states, selecting actions, and learning from the outcomes. Through iterations of trial and error, Ribabot aims to become progressively smarter and more adept at playing the game.

The construction of Ribabot involved implementing a reinforcement learning algorithm, specifically Q-learning, in Python. Challenges arose in fine-tuning the algorithm, determining reward structures, and effectively integrating it with the game environment. Despite these hurdles, we're proud of Ribabot's functional implementation and the insights gained into reinforcement learning techniques.

Through Ribabot's development, we've deepened our understanding of reinforcement learning and its practical application in game AI. Moving forward, our focus is on refining Ribabot and exploring advanced reinforcement learning techniques to enhance its performance and adaptability. Ultimately, we aim to create a highly skilled and adaptive AI bot capable of competing at a high level in the game environment.

Built With

• python