Artificial Intelligence in Games
Artificial intelligence in games is usually used for creating player’s opponents. Opposite to this, the objective of intelligence amplification is rescuing the player from the boredom of repetition and letting him focus just on the interesting aspects of the game. The player gives high-level strategic orders, the computer-controlled units take care of detail. At the same time, the full detail and dynamics of the game is maintained with the computer control of detail, rather than lost through abstraction. There are still bullets flying, rather than tiles shifting. In addition to this, intelligence amplification is fully applicable to multi-player games.
Let’s illustrate this concept on an example of a tactical game. The player is in command of a number of squads, each composed of several individual soldiers. The player’s orders refer to the whole squad, whereas the members of the squad choose and adjust the formation. Each individual member of the squad is intelligent, trying to maximize his efficiency and minimize his exposure.
The player can give his squad two kinds of orders: explicit and implicit. Most games support only explicit orders: move, attack, guard, build, etc. Unlike explicit orders, implicit orders transmit information from the player to the units and assists them in making better autonomous decisions. For example, a player might want to inform his squad that he expects that opponents will approach from the east, rather than the west, by drawing an arrow of expected attack. Alternatively, the player might want to draw a circle where he expects the ambush.
We perceive other people as intelligent, because we understand their decisions. We can introspectively reason about their motivations and intentions. If we do not understand an aspect of their behavior, we can ask. It is different with animals, but because their emotional responses are similar to human ones, we still perceive them autonomous, alive, and intelligent. The artificial computer creatures all too often end up as emotionally dull soulless bitmaps sliding around the screen. To influence the player to perceive the creatures as intelligent, he has to be provided more insight on their actions, intentions, thoughts and emotions.
Emotions are simple to model. Joy is positive feedback, bursting after successful completion of a hard task, and then leveling off. Fear emerges in face of uncertainty and danger, but in a temporarily safe situation. We can see that most emotions applicable to computer games can be derived as functions of concepts such as: success/failure, extent of danger/safety, expectations, etc. Other emotions, apart from joy and fear, are trust, surprise, fear, disgust, and anticipation. Diversity is important: two individuals never have identical emotional response, so they need to be randomized. Emotions are contagious: in a happy atmosphere, everyone becomes happier.
It is appropriate to visualize emotions with stereotypical animation. People express fear by rapid head motion, low posture, and bulged eyes. Happy individuals are smiling, have a straightened body, move in a slow and graceful way, while groups bunch up. Sad creatures look downwards and move slowly.
Although the intentions, perceptions and motivations of the artificial creatures could be described with language, this approach is far too cumbersome for most games. We are not creating artificial friends; we are just trying to enrich the player’s environment. Intentions can be easily visualized with a graphical language. In a tactical game, the map can be tagged with place flags such as “good defensive position”, “dangerous passage”, etc., in addition to vectors indicating directions. Alternatively, the route taken might be visualized schematically. This way the player understands how his units intend to act, what information are their decisions based on, what could happen, and when is it really worth detailing or correcting the order.
Emotion in current computer games is either non-existent or absolutely superficial (state: running away, state: fighting aggressively, state: waiting for the enemy). But games themselves are intended to provide a very different kind of fun than drama, and they do not require the full spectrum of emotion. This is the framework where my ideas are intended to fit.
I’m trying to encourage a small evolutionary, step towards slightly better modeling of emotions like happiness, fear, and show reasons why this would enhance gameplay in ordinary action and strategy games. And modeling happiness and fear is not hard. Also, I strongly dislike the scripted emotions, and prefer emotions at a continuous scale, depicted through parameters in 3D animation.
Finally, psychological transparence is a wider term than emotion. It includes giving the player some insight in the cognition of artificially intelligent entities. For example, if you don’t understand why your units are moving into bushes, you might disagree, and declare them stupid. If they somehow explained why they are doing this, the player would understand.