In an instinctive system, all of its beliefs (or knowledge) are instinct, i.e., innate relations that link goals to actions. The system behaves by reacting to current needs or signals in predetermined manner, and the experience of the system has little impact on the stimulus-response connection. Consequently, the capabilities of an instinctive system remains constant over time. Most animals and conventional computer systems can be put into this category.
In an intelligent system, most of its beliefs (or knowledge) are summarized experience. Even if there are still innate stimulus-response connections, they are typically modifiable by the system itself. Consequently, the capabilities of an intelligent system changes, and normally increases, over time. Most human beings and some computer systems can be put into this category.
Please note that, defined in this way, an intelligent system is not necessarily more capable than an instinctive system. Intelligence does not indicate capability, but change in capability. Whether (or how much) a system is intelligent is not determined by what the system can do, but what it can learn.
Adaptation will improve the system's capability only when the future is indeed similar to the past. It means that adaptive systems only live better in relatively stable environments, where things may change, but not too much. In environments where changes happens randomly (that is, no pattern or law can be recognized), all systems are equally bad, adaptive or not.
Designing an adaptive system is quite different from designing an instinctive system. In the latter case, first the designer need to identify the goal of the system, then give the system sufficient ability and knowledge to achieve the goal. In the former case, the designer into gives the system the knowledge and ability that allow the system to obtain new knowledge and ability by itself from its experience.
To check if a system is truly adaptive, we should not check whether (or to what extent) its goal is achieved, but to check whether (or to what extent) its goal will be achieved if the future situation is consistent with the system's past experience.
Being adaptive is closely related to being able to work with insufficient knowledge and resources. A system with sufficient knowledge and resources (with respect to its goals) has no need to adapt; a non-adaptive system treats its knowledge and resources as sufficient, for all practical considerations.
The ability of working with insufficient knowledge and resources is a defining property of intelligence, and many other properties of intelligence can be derived from it.
There are different types of rationality, each based on a different assumption on its applicable situation. Whether to assume insufficient resources differentiates certain definitions of rationality from some others that assume otherwise.
Since all human beings start with similar innate capability, their capability at a certain age is highly correlated to their learning ability, and that is why the notion of IQ makes some sense. However, since a computer system can be built with various innate capabilities, what the system can do at a moment and what it can learn at the time have little correlation.
The above working definition of intelligence can be applied to other fields like animal intelligence, alien intelligence, and community intelligence.
All these fields support the opinion that "intelligence", as an ability abstracted from multiple fields, is about whether, or how much, a system can improve its problem-solving capability by adaptation, that is, learning from its past experience.