Row 4170

Row ID: 4170 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 4170 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

Thank you for taking the time to respond!

Yes, I know it’s possible to feed enemy pos directly to the model, but I don’t want this to access any game memory at all. I don’t know much about game hacking anyway and am interested in the creative challenge.

I ended up getting it to work relatively okay (it doesn’t bump into walls ever, but it’s not going pro anytime soon). I used a cnn and was taking a 200x200 picture of the minimap with a filter to find edges, saved the data about what keys i pressed during that screenshot, and separated the screenshots into folders that corresponded with that keybind.

I like this solution because I can influence the training easily to have it play a certain way. Things like staying on headglitch spots, jiggle peaking, jump peaking, etc are automatically learned using this method.

I am starting to worry about it’s ability to process info fast enough. The movement model is plenty fast, but I still need to work on the target identification and aiming. My current solution was to have the movement(including simple mouse movements for direction change) and targetID/aiming models run on separate threads since they don’t really need to communicate anything. The bot just needs to farm deathmatch kills, not understand anything else in the world like health, ammo, objective, etc.

Although, I might pass it the ammo count so it can become defensive once it recognizes it should reload soon.

Does that seem like an okay solution? Only have like 4 days of NN experience lol so I’m sure it’s not optimal, but I can’t think of any reason it won’t be good enough. Thanks 🙏🏽

FieldValue
text Thank you for taking the time to respond! Yes, I know it’s possible to feed enemy pos directly to the model, but I don’t want this to access any game memory at all. I don’t know much about game hacking anyway and am interested in the creative challenge. I ended up getting it to work relatively okay (it doesn’t bump into walls ever, but it’s not going pro anytime soon). I used a cnn and was taking a 200x200 picture of the minimap with a filter to find edges, saved the data about what keys i pr…
label r/neuralnetworks
dataType comment
communityName r/neuralnetworks
datetime 2024-04-03
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url_encoded Z0FBQUFBQm5Lak9GVTk3YmJnNC1xQndRVkxMSlBpUjdENm9FdTZlYkZmWUR1Y2xlbVBLLTBHbXNhem92d1lOU3U2VlRJWVJKSlQ3QnJOMjlsOWVoTWxrQnFwZmNYVmY3el8zUTE3Y3RJcFMtbm80MWEyQ01oNjMxamdmbkxrTGVEa2lrcFppY2tPMHRkVzNYaERyZVFqdTRwWFJQSHlnY0trU3BZN1AyOGZnbk1ZLXd6X2F4LUJkNEhtRVNxVENqMFhHX1ZXOVFDTjRCSmVobVNFUGF6WTZ5ZDA4NkwxdVdkUT09

Raw Record

{
  "text": "Thank you for taking the time to respond!\n\nYes, I know it’s possible to feed enemy pos directly to the model, but I don’t want this to access any game memory at all. I don’t know much about game hacking anyway and am interested in the creative challenge. \n\nI ended up getting it to work relatively okay (it doesn’t bump into walls ever, but it’s not going pro anytime soon). I used a cnn and was taking a 200x200 picture of the minimap with a filter to find edges, saved the data about what keys i pressed during that screenshot, and separated the screenshots into folders that corresponded with that keybind. \n\nI like this solution because I can influence the training easily to have it play a certain way. Things like staying on headglitch spots, jiggle peaking, jump peaking, etc are automatically learned using this method. \n\nI am starting to worry about it’s ability to process info fast enough. The movement model is plenty fast, but I still need to work on the target identification and aiming. My current solution was to have the movement(including simple mouse movements for direction change)  and targetID/aiming models run on separate threads since they don’t really need to communicate anything. The bot just needs to farm deathmatch kills, not understand anything else in the world like health, ammo, objective, etc.\n\nAlthough, I might pass it the ammo count so it can become defensive once it recognizes it should reload soon. \n\nDoes that seem like an okay solution? Only have like 4 days of NN experience lol so I’m sure it’s not optimal, but I can’t think of any reason it won’t be good enough. Thanks 🙏🏽",
  "label": "r/neuralnetworks",
  "dataType": "comment",
  "communityName": "r/neuralnetworks",
  "datetime": "2024-04-03",
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}
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