Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   describe a hierarchical method for procedurally generating maps using Markov chains. Our method takes as input a collection of human-authored two-dimensional maps, and splits them into high-level tiles which capture large structures. Markov chains are then learned from those maps to capture the structure of both the high-level tiles, as ll as the low-level tiles. Then, the learned Markov chains are used to generate new maps by first generating the high-level structure of the map using high-level tiles, and then generating the low-level layout of the map.  validate our approach using the game Super Mario Bros., by evaluating the quality of maps produced using different configurations for training and generation.
['Sam Snodgrass', 'Santiago Ontañón']
I am writing a research paper on a idea A hierarchical approach to generating maps using Markov chains
[{"from": "human", "value": "I am writing a research paper on a idea A hierarchical approach to generating maps using Markov chains"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   describe a hierarchical method for procedurally generating maps using Markov chains. Our method takes as input a collection of human-authored two-dimensional maps, and splits them into high-level tiles which capture large structures. Markov chains are then learned from those maps to capture the structure of both the high-level tiles, as ll as the low-level tiles. Then, the learned Markov chains are used to generate new maps by first generating the high-level structure of the map using high-level tiles, and then generating the low-level layout of the map.  validate our approach using the game Super Mario Bros., by evaluating the quality of maps produced using different configurations for training and generation."}]