So is this trying to use a learning algorithm that incrementally improves Graphics every time the AI answers "simulated"? Is the goal to improve graphics enough to trick the AI in to thinking a "simulated" image is in fact a "real world" image?
I had a similar idea but for martial arts. in unreal engine the character can be made to move, then the code can direct the character to interact with other characters in a dance type of mechanism, where the dance means the two characters interacts in a method the developer made for instance the enemy of a rpg hero game follows the enemy to attack him.
so the character has a skeleton and can be made to interact with the other bot character to make the two characters bones of their skeleton interact.
then the skeleton can have attributes like strength, and weight, real world physical attributes. so when the two bots interacts the idea is they are made to test martial arts ideas.
then the two bots can have different martial arts like wrestling or judo or mma or kung fu and this can prove what works and what doesn't better than a real world boxing match. and its applicable to AI because you can find out the intelligence using game mechanics and see the results in the virtual world. bots don't feel fear or pain they just act.
so for your idea maybe you need something similar.
So is this trying to use a learning algorithm that incrementally improves Graphics every time the AI answers "simulated"? Is the goal to improve graphics enough to trick the AI in to thinking a "simulated" image is in fact a "real world" image?
I had a similar idea but for martial arts. in unreal engine the character can be made to move, then the code can direct the character to interact with other characters in a dance type of mechanism, where the dance means the two characters interacts in a method the developer made for instance the enemy of a rpg hero game follows the enemy to attack him.
What you are describing is animation, collision, and conditional behavior (boolean logic). That is a contrast to actual Machine Learning and Artificial Intelligence.
This looks like a model we can implement for a chabot. I have actually worked on a more advanced algorithm for Fraud Prevention using AI techniques, including supervised and unsupervised machine learning algorithms, to distinguish between good and malicious bots in real-time, making it uniquely capable of identifying known and emerging attacks. Because the conversation bots can be able to communicate just as a real world data and must be able to identify if it's a real human interacting with the platform or a bot. We are a chatbot development company and we have come across several instances where the bots were able to overcome all the firewalls implemented by the website. Only an advanced AI algorithm can fix these issues.
