From the early AI pioneering stage the research emphasis has been on developing machines with intelligent behaviour. Machine intelligence however is hard to achieve.
Some of the specific characteristics of intelligent behaviour include the ability to do the followings.
Learn from Experience and Apply the Knowledge Acquired from Experience: Learning from past situations and events is a key components of intelligent and is a natural ability of human who learn by trial and error. This ability however must be carefully programmed into a computer system. Today researchers are developing systems that can learn from experience.
Handle Complex Situations: People are often involved in complex situations. World leaders face difficult political decisions regarding terrorism conflict global economic conditions hunger and poverty. In a business setting top level managers and executives must handle a complex market challenging competitors intricate government regulation and a demanding workforce. Even human experts make mistakes in dealing with these situations. Developing computer systems that can handle perplexing situations requires careful planning and elaborates computer programming.
Solve problems when important Information is Missing: The essence of decisions marking is dealing with uncertainty. Often decisions must be made with little information or inaccurate information because obtaining complete information is too costly or impossible. Today AI systems can make important calculations comparisons and decisions even when information is missing.
Determine What is Important: Knowing what is truly important is the mark of a good decision maker. Developing programs and approaches to allow computer systems and machines to identify important information is not a simple task.
React Quickly and Correctly to a New Situation: A small child for example can look over a ledge or a drop off and know not to venture too close. The child reacts quickly and correctly to a new situation. Computers on the other hand do not have this ability without complex programming.
Understand Visual Images: Interpreting visual images can be extremely difficult even for sophisticated computers. Moving through a room of chairs tables and other objects can be trivial for people but extremely complex for machines robots and computers. Such machines require an extension of understanding visual image called a perceptive system. Having a perceptive system allows a machine to approximate the way a person sees hears and feels object. Military robots for example use cameras and perceptive systems to conduct reconnaissance missions to detect enemy weapons and soldiers. Detecting and destroying them can save lives.
Process and Manipulate Symbols: people see manipulate and process symbols every day. Visual images provide a constant strum of information to out brains. By contrast computers have difficulty handling symbolic processing and reasoning. Although computer excel at numerical calculations they are not as good at dealing with symbols and three dimensional objects. recent development in machine vision hardware and software however allow some computers to process and manipulate symbols on a limited basis.
Be Creative and Imaginative: Throughout history some people have turned difficult situations into advantages by being creative and imaginative. For instance when hipped defective mints with holes in the middle an enterprising entrepreneur decided to market these new mints as life savers instead to returning them manufacturer.
Use Heuristics: For some decisions people use heuristics ( rules of thumb arising from experience) or even guess. In searching for a job you might rank the companies you are considering according to profits per employee. Today some computer systems given the right programs obtain good solutions that use approximations instead of trying to search for an optimal solution, which would be technically difficult or too time consuming.