Intelligent flash game

All Rights Reserved. Product List. Click to Get Advanced Editions. SWF Editor. Features Solution. One of the most widely used tricks, called the Finite State Machine FSM algorithm, was introduced to video game design in the s. In a FSM, a designer generalizes all possible situations that an AI could encounter, and then programs a specific reaction for each situation.

For example, in a shooting game, AI would attack when human player shows up and then retreat when its own health level is too low. A simplified flow chart of an FSM is shown in the following image Figure 1.

In this FSM-oriented game, a given character can perform four basic actions in response to possible situations: aid, evade, wander and attack.

An obvious drawback of FSM design is its predictability. MCST embodies the strategy of using random trials to solve a problem. This is the AI strategy used in Deep Blue, the first computer program to defeat a human chess champion in For each point in the game, Deep Blue would use the MCST to first consider all the possible moves it could make, then consider all the possible human player moves in response, then consider all its possible responding moves, and so on.

After repeating this process multiple times, the AI would calculate the payback and then decide the best branch to follow. After taking a real move, the AI would repeat the search tree again based on the outcomes that are still possible. In video games, an AI with MCST design can calculate thousands of possible moves and choose the ones with the best payback such as more gold. A similar algorithm has also been applied in many strategy games.

However, since the possible moves are much more than in chess, it is impossible to consider all of them. Instead, in these games the MCST would randomly choose some of the possible moves to start with. Therefore, outcomes become much more uncertain to human players. For example, in Civilization , a game in which players compete to develop a city in competition with an AI who is doing the same thing, it is impossible to pre-program every move for the AI.

The AI then performs the MCST to calculates the overall payback of each of these moves and chooses whichever is the most valuable. A simplified flow chart of the way MCST can be used in such a game is shown in the following figure Figure 2.

In these games, the evolution of a situation is never predetermined, providing a fresh gaming experience for human players every time.

Although AI designers in the s worked very hard to make NPCs look intelligent, these characters lacked one very important trait: the ability to learn. The reason most NPCs do not exhibit the capability to learn is not only because it is difficult to program machines to learn, but also because most designers prefer to avoid any unexpected NPC behaviors that could impair the experience of a human player. In this game, the player can train a digitized pet just like he or she may train a real dog or cat.

Using shooting game as an example again, a human player can deliberately show up at same place over and over, gradually the AI would attack this place without exploring. Until now, virtual pets games still represent the only segment of the gaming sector that consistently employs AIs with the ability to learn. The short answer is yes, they can. In terms of possible moves and number of units to control, RTS games are far more complicated than more straightforward games like Go.

In RTS games, an AI has important advantages over human players, such as the ability to multi-task and react with inhuman speed. In the future, AI development in video games will most likely not focus on making more powerful NPCs in order to more efficiently defeat human players. Hangman The classic Hangman word game: guess the word before the man hangs. Daily Word Search Everyday new word search puzzles in 3 different sizes. Daily Stream Everyday new Stream levels in 6 different sizes, can you solve all?

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