loreal
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- Joined
- Oct 1, 2014
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Hello everyone,
I would like to initiate a discussion on the use of Artificial Intelligence (AI) for modifying and optimizing maps in Remere's Map Editor (RME) for Open Tibia. I've been thinking about this idea for some time, and I believe that with recent advancements in AI technology, this possibility is increasingly becoming a reality.
Based on my research, here are some possible approaches:
1. Machine Learning:
One way to do this would be through the use of Machine Learning techniques. This would involve training an AI on a large amount of existing maps, allowing it to learn the characteristics of 'good' and 'bad' maps. Over time, the AI could then be used to generate new maps based on this knowledge, or modify existing maps to improve them. There are many Machine Learning techniques that could be used for this, from Convolutional Neural Networks to understand the spatial structure of maps, to genetic algorithms for optimization.
2. Procedural Generation:
Another approach would be procedural generation. Instead of training the AI on existing maps, we could program it with a set of rules and guidelines to create maps. Procedural generation is common in many games and could be an interesting way to create new maps that are unique yet still follow a certain design pattern.
3. Combination of Machine Learning and Procedural Generation:
I believe the most exciting approach would be to combine both methods. We would use Machine Learning to understand what makes a map 'good' or 'bad,' and then use this information to inform the procedural generation. This would allow the creation of unique maps that are also optimized for gameplay.
Challenges
There are several challenges we would have to overcome to implement this idea:
I would like to initiate a discussion on the use of Artificial Intelligence (AI) for modifying and optimizing maps in Remere's Map Editor (RME) for Open Tibia. I've been thinking about this idea for some time, and I believe that with recent advancements in AI technology, this possibility is increasingly becoming a reality.
Based on my research, here are some possible approaches:
1. Machine Learning:
One way to do this would be through the use of Machine Learning techniques. This would involve training an AI on a large amount of existing maps, allowing it to learn the characteristics of 'good' and 'bad' maps. Over time, the AI could then be used to generate new maps based on this knowledge, or modify existing maps to improve them. There are many Machine Learning techniques that could be used for this, from Convolutional Neural Networks to understand the spatial structure of maps, to genetic algorithms for optimization.
2. Procedural Generation:
Another approach would be procedural generation. Instead of training the AI on existing maps, we could program it with a set of rules and guidelines to create maps. Procedural generation is common in many games and could be an interesting way to create new maps that are unique yet still follow a certain design pattern.
3. Combination of Machine Learning and Procedural Generation:
I believe the most exciting approach would be to combine both methods. We would use Machine Learning to understand what makes a map 'good' or 'bad,' and then use this information to inform the procedural generation. This would allow the creation of unique maps that are also optimized for gameplay.
Challenges
There are several challenges we would have to overcome to implement this idea:
- Collecting Training Data: We would need a large amount of existing maps to train the AI. Collecting these data could be a challenging task.
- Code Adaptation: The RME code, available at GitHub - hampusborgos/rme: Remere's Map Editor (https://github.com/hampusborgos/rme), would have to be adapted to allow the AI to interact with it.
- Training Time: Training an AI to understand and create maps could take a significant amount of time, depending on the complexity of the map and the amount of data available.
- Validation and Testing: Checking whether the maps generated or modified by the AI are playable and fun will be a significant challenge.
