The point is simply that real Artificial Intelligence is not successful, in general, in providing a satisfying behavior for agents in games, thus what is created is usually just a simulation of intelligence. Game AI does not aim to create a real imitation of intelligence that can actually learn and take over the world, but to provide a fun and slightly challenging experience for the player.
Game AI is focused on the player experience, not on academic relevance.
Why even have a forum for 'AI' then if there is no need? Plenty of online scripting 'tricks' already to do everything needed, right??
'Player Experience' is obviously not what it could be/aught to be, and pushing the 'smarts' ahead is being sought (to give us decent games more complicated than the typical 'blast-fest' we have been 'in general' stuck with).
To do that we have to move closer to 'real' AI, and lately we have started to have the processing resources to do so (lack of that was the old excuse).
The new excuse - its too complicated/too difficult/too long to build the logic... (as Ive repeated - if the 'learning' isnt in-game, it can still be used for the development phase to build the volumes of static logic required for a mere increment of 'simulation of intelligence' ).
Part of 'real' AI IS using a 'learning process', which CAN be implemented by clever programming to overcome the above hurdle (sufficiently).
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Problem - games where NPC usually stand like mannekins oblivious to actions you take or do something irrelevant because the NPCs werent programmed to handle you doing THAT (programming cost too much, proper testing is prohibitive, etc.. too much trouble to bother with more than the most expected player actions in a game situation) .
Problem - games that run EXACTLY the same way every time because they are heavily choreographed - the situations cannot be mutatable (to give additional replay value) because it breaks the specific behavior logic matching each heavily choreographed situation. Similarly, the number of 'situations' in any particular game is getting fewer because of the cost is so high for each one.
Solution - would be a tool to assist building of situation analysis logic, which would run thru real game situations to build generalized behavior logic. Presenting the user with real game situations and asking what factors were important for the decision and then what an appropriate (re)action was proper to the state of those factors. After a while, similarity of situation would have the system telling you what it estimates the important factors to be and its proposed reaction -- for the user to confirm or make corrections (to elaborate the logic for a special/additional cases). A possible extension of that is 'observing the player' and noting the actions taken in normal play (to build cases for the 'proper reactions').
That 'learning system' could speed up the logic building by many (many) times (cost $$$ effective over hand coding and testing ). That general logic would be applied to all game 'scene' situations (eliminating alot/most of scene custom logic - at some point the built-up general logic has a cross-over point of cost effeciveness over using custom built logic). Something like that is already done with common NPC scripting logic, but this goes beyond in versatility (and the scripting is expensively hand crafted).
An associated tool would be traversing the existing 'factoring/reacting' logic to see where gaps exist, to guide the 'situation selection' to have sufficent coverage of possible cases. (the system suggests combinations it needs after it has noted what 'factors' are in the game.)
Another tool helps create those in-game 'situations' - some kind of arena composer to easily/quickly drop desired game elements together to test (including avatar state). Optimizing this part of the process speeds things up (finding 'likely' situations can be thru extracting them from recordings of players playing the game).
All of these tools would be designed to take 'hints' to start off the knowledge base, with the system becoming more and more automated as the data becomes mature, to the point where the user is tweaking' the logic when needed.
The Game's development would have the NPCs logic changing and growing as the entire process moves forward (in complicated games NPCs react to each other when they react to the players actions...) you would have iterations to evolve all the NPCs game logic as each one got better. (The system also builds test cases that can short-cut rebuilding the logic when other developers suddenly decide to drasticly change the game mechanic logic)
A further complexity is NPCs 'cooperating' against the player or assisting the player (a real source of belief breaking mal-behavior in current games). It would be a real improvement to have these cases better handled (via alot of the neccessary logic...).
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SO the 'AI' (or rather intelligence simulation) comes in as not just automating the process but 'intelligently' automating the logic building process to assist the user. Another aspect is that many games have VERY similar game mechanics so that the 'knowledge base' for subsequent games may only take 'tweaking' and thus reusing a bulk of the logic (and/or the general test cases used).
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I looked at AI for a project years ago and came to the conclusion that creating the AI system (including planners and FSM based solvers) itself is trivial compared to the effort to build up the behavior logic for a decently complex game. The human component of the process is the choke point, and any real improvement in 'Game AI' will have to address that problem.
--------------------------------------------[size="1"]Ratings are Opinion, not Fact