Life in Wireframe

Most of us are familiar with the term Artificial intelligence or AI, which has been around since the 1940s. It's not to uncommon in Hollywood when it comes to doomsday films as The Terminator, AI(the movie), I Robot or Eagle Eye. So is AI going to doom us all? Well, no I don't think so ... the human race can handle that all by them selves. The area artificial intelligence is not strictly emergent, but emergent behavior underlays AI so I'm going to have it as a topic anyway because it's such widespread and basicly tries to emulate nature and the human brain.

Some techniques are strictly bruteforce, as many calculations as possible under an estimated time. For example - Deep Blue, the first computer to beat the reigning world champion in chess Garry Kasparov in 1997. The "AI" used for this task was mainly to foresee an amount of moves to a certain depth and make the most logical choise. This is not the kind of AI we will be focusing on, however emergent behavior underlays computational intelligence in a way.

As I've stated before, this blog if you may is for exploring thoughts around life and the emergent behaivor that sourrounds it.

However, AI is about making choises which best fits the situation. Wether it's playing chess, walking down stairs, or using abstract objects the AI makes choises based on what it "knows" about its environment. How it gathers that information can be done through numerous methods, or often in combination of methods.

Hold on to your hats or brifes, the following will contain many field buzzwords that may be confusing. I'm going to cheat a little bit and actually use the wiki approach dividing AI into three describing areas because we get a good preview of the subject, but avoid diving to deep into it.

Problems

Yes, every area has its sets of problems and AI has many. Why? Well for starters - we don't know how the object works that we are trygin to simulate. I'm talking about the worlds most advanced super computer which is replicated into about 6 billion copies. You guessed it - The brain.

Early AI researchers developed algorithms that imitated the step-by-step reasoning that humans were often assumed to use when they solve puzzles, play board games or make logical deductions

But we humans are far more complex and use our emotions and intuitive judgment as variables in the equation when we are faced with a problem or task. Our brain is not a statemachine which itterates through possible answer, its more of a quantum machine which calculates millions of options simultaneously, and into that mix also apply our personal experienc ande emotions. There is no chance of simulating that(yet). AI however has several fields to coup with these issues and tries to handle the same input that we humans get from our surroundings to make adjustments to it.

The Planning methology is to set a goal and reaching it. As we humans do when wee need to get from point A to point B. Here we can apply emergent behaivor as a model through Evolutionary algorithm and Swarm intelligence, much like the Boids approach we've been discussing. The natural next step is Learning, which has been the central research in AI from the very beginning. Without going into it we here apply Unsupervised learning, Supervised learning and reinforcement learning which are different approaches to solve the same problem in different situations. We have Natural language processing to deal with communications between digital system and humans through regular language. We've actually come quite far on this one! The last thing I'm going to list as a AI problem in Perception, input from our surroundings through our five sences. This is a big one in robotics where of course the visual perception has most focus. We are talking facial recognition and object recognition to build a internal representation of the world.

Approach

There are several different approaches where not all play well with eachother. AI is not a defined researcharea which relies on theorems like mathematics. What "AI" stands for can't be explained in a single sentence. First of all it depends on the angle you are looking at it - is it from a psykological view, or something else. Is the term AI and the result it produces of the same value by all standards? Well the quick answer is - No. Here are some examples how to approach AI. You will notice that most research are based around the 1970s or earlier so this is something that's been around before we got computerized.

In the 1940s and 50s research was made for exploring the possibilty of reducing human AI to symbolic representation. There were Cognitive simulation where psycological experiments were used for developing programs that simulated human problem solving techniques. This laid the foundation for Cognitive science which later formalized the research. Others claimed that simulating the human brain wasn't enough, and abstract reasoning och problem solving were more fitting - Logical based intelligence. Using formal logic later came to be the backbone in logical programming which evolved to programming languauges as Prolog. In later years when computers were more advanced a different type of AI emerged. It is now known as Knowledge based intelligence. Having more system memory the researchers were able to construct programs that held more information, and therefor beeing able to access more data than just split second input. From here the first "real" successfull AI programs were deployed and they are formaly know as expert systems. For example a doctor could use symptoms on a patient as input and get a list on possible diagnoses as a result. Though expert systems should never be an absolut factor when making decisions. It should rather be a support system taken under advice. An exceptional scenario is when subscribing medication for a patient. A expert system could instantly prevent a doctor from subscribing drugs which should not be mixed with eachother, or hinder a obvious wrong dosage.

The sub-symbolic approach came to be of greater interest in the 1980s when little faith was shown to regular symbolic AI when focusing on seriuous perception, pattern recognition and robotics. We now touch the area which this site focus on - Computional intelligence. Using more non-symbolic methods as neural network, fuzzy systems and evolutionary computing researcher were able to embody the AI more according to the embodied mind thesis, a related field in cognitive science. Roughly speaking it sais that the AI is determined by it's form of "human" body. This makes sence looking a the Boid system, an abstract method with a set of rules which is embodied by an agent or avatar.

Now it's time to stop ... you should now have a good idea of the foundation of AI in genreal terms. AI is what we do here on this site, but we only focus on selected parts ... the interesting ones =) But never the less, one should know the hole picture rather than a small corner.

- Tobias