In simpler words, nonanticipatory systems can “take into account” only past and present, and cannot base their behaviour/decisions on future expectations.

Nonanticipatory systems are also known as causal systems.

In this post I’ll try to figure out (primarily for myself) what is Artificial Intelligence.

Evidently, the “artificial” part requires no explanation, and the real problem is only with the “intelligence” part.

An extremely over-simplified, and actually incorrect definition would be “Intelligence is the ability to think logically”. Evidently, logic cannot be the sole basis of intelligence, at least because intelligence requires an ability to comprehend the environment, not only deduct. Moreover, logic itself is not an ultimate intelligence resource – it cannot explain the environment. Even planning an experiment – a generic method of studying the environment – requires not only logic, but also some kind of stimulus to learn the environment (possibly derived from the adaptation requirement which, in turn, is one of the mechanisms of self-preservation and self-defense).

One more definition I came across was “Intelligence is the ability to act purposefully in unknown situations“, which is not strictly correct. If the situation is unknown, it might be not intelligence, but instincts defining actions. If we omit the ambiguity of “unknown situation”, the definition seems good: if “unknown situation” has long enough time duration, and the tested (observed) being is able to find the dependencies between the elements of the previously unknown environment, and use those dependencies to the benefits of the being, then that being is intelligent.

In my opinion, one of the best definitions would be: “Intelligence is the possession of a model of reality and the ability to use this model to conceive and plan actions and to predict their outcomes. The higher the complexity and precision of the model, the plans, and the predictions, and the less time needed, the higher is the intelligence” (taken from transition). This definition should be enhanced with “the ability of intelligent being to acquire the model of reality”, because otherwise intelligence is incomplete. This definition appears correct. The only problem is that it also does not allow the quantification of intelligence.

The above definition is also what is described in wikipedia as Strong AI: “Strong AI [approach] supposes that it is possible for machines to become sapient, or self-aware, but may or may not exhibit human-like thought processes”. Strong AI is opposed to Weak AI, the proponents of which consider the creation of self-aware and reasoning machines impossible, and leave only minor functions to AI.

The AI is sometimes associated with the so-called Singularity, which implies that the creation of AI (evidently, Strong AI) will lead to the loss by humanity of its leading and defining role. As a result, AI will in some way supersede mankind, and, eventually, mankind may be isolated to degrade, or destroyed by AI.

In the light of permanent improvements in AI-related fields (such as various recognition tasks) the so-called AI Effect: “The AI effect is a term for the tendency for individuals to discount advances in artificial intelligence after the fact”.

Thus, “Artificial Intelligence is the ability of a [human-]created entity to acquire the model of reality based on observations and interactions with reality. Artificial Intelligence possesses the created models of reality, and is able to use the models to conceive and plan actions and to predict their outcomes. The higher the complexity and precision of the models, the plans, and the predictions, and the less time needed, the higher is the strength of the Artificial Intelligence“.