Scenarios for AI in Digital Media
Computer Science and Digital Media are interrelated in many ways. Digital Media harness Computer Science in many ways. Below are some scenarios where AI and Digital Media intertwine.
You are creating 3d real times strategy (RTS) game. This game allows for the user to create a large army by building up different squadrons of various soldiers (archers, footman, horseman etc.) When the soldiers are created you want the user to be able to attack a computer controlled fortification or army. To make the game more enjoyable you wish the army to adapt to the play style of the user and be able to learn from their actions to better prepare them in future encounters. How can A.I help in this situation?
A.I. would be able to handle the group behavior necessary to have a large army respond to each other and their environments. This would be done through the use of agent technologies similar in method to Massive and the Artificial Life project. These technologies use Fuzzy Logic to allow agents to react similarly to humans. The ability for software to learn from users makes games more enjoyable and tailors the experience to each user. This A.I. technology harnesses the power of Machine Learning
You are creating a 3d animation that requires you to have a scene of thousands of character in battle in several shots. Due to the time constraints you do not have the ability to hand animate each character. You need a system that allows you to have many characters use animations you create to interact with each other without seeming repetitive and all responding the exact same way. How can A.I. help in this situation?
This has been a dilemma for many animation and visual effects studios. Hand animation individual soldiers in an army takes an extreme amount of time. A.I. would be a great solution to this problem. Agent technology would allow you to create agents that would respond to each other and the environment. This would require that you create an animation (or multiple animations) for each action that an agent can go through. These actions would be called by the agent's brain. The agent brain uses Fuzzy Logic in order to make decisions as to what action should be called.
Massive is a software package that has been used several times for this very purpose. Lord of the Rings, King Kong, Evan Almighty and The Chronicles of Narnia all use Massive to create their large crowd scenes. As mentioned above, the Artificial Life project would also be viable for creating a realistic crowd animation.
You wish to create a 3d animation that where you want your character to respond to real world physics at certain points in while adhering to your animation at other points in time. For example you want a character to be running down the road, get hit by a car, and then land safely on its feet. You want to be able to control the animation before the character was hit by the car and once it lands however in between them you wish for physics to take command as long as it can achieve the starting pose you defined after it hits the road. How can A.I help here?
Because there is no one solution that provides an exact solution to this problem it is hard to come to a solution for this dilemma. Through the use of genetic algorithms the computer can discover a solution that works Genetic algorithms are one of several types of evolution computation. A system like this is the basis of Natural Motion's Endorphin. Genetic Algorithms are a subsection of Evolutionary Computation
You create a online system that allows a user to attach tags to a movie file they upload. These movie files become nodes that are able to be connected to each other to create a branching non-linear story path. You want to allow the user to find paths based on length as well as creating a system that allows the user to make a short sentence that will be used to search for a path that will most resemble the sentence. How can AI help to solve this pathfinding?
Because the English language has many words with the same meaning. Because of this, it becomes important to break down these words using Natural Language Processing and then gather all the synonyms to create a large database of similar words to compare to the tags in order to find a path. Natural Language Processing (NLP) is s subsection of Machine Learning
You wish to make a installation game that will allow for multiple users to interact at the same time. This piece should allow multiple users to interact with each other over a single screen without the need for any input device (mouse, joystick, keyboard etc). Also, to make the game more interesting you want to remove the need for any graphical interfaces to interact with the program but instead be able to use different gestures in order to perform different actions. What would AI be able to offer as a solution to this problem?
A multi-touch display would be an ideal solution for the hardware issue of this dilemma. These units are touch sensitive displays that allow for multiple points of contact simultaneously. To allow for multiple users, AI must be used to differentiate each one based on proximity and time of touch. This not only allows for a more intuitive interaction but also provides the ability for multiple users to interact with each other and work simultaneously on one system. Gesture recognition is an important part for making this system intuitive. This can be done through training the computer program to recognize each of the gestures by harnessing the techniques of Machine Learning.