Shannon, August 31, 1955: "We propose that a 2 month, 10 man study of artificial intelligence be carried out during the summer of 1956 at Dartmouth College in Hanover, New Hampshire. The study is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it"2.
Centuries before McCarthy coined the term AI, early traces of AI emergence can be found during the time of the ancient Greek Gods; the myths of golden robots created by a Greek God; Hephaestus3. The attempt to create AI could also be seen in the form of sacred statues worshipped in Egypt4 and Greece5. In medieval times, existence of AI was supported by claims made by alchemists e.g. Paracelsus created artificial beings6. Other examples of AI can be seen from the realistic clockwork imitations of human beings built by people like Yan Shi7, Hero of Alexandria8, Al-Jazari9 and Wolfgang von Kompelen10. AI was also present in famous modern fiction such as Mary Shelley's classic Frankenstein and the film Artificial Intelligence:A.I. The modern history of AI includes the birth of computers that were intelligent enough to solve word problems in algebra, proving logical theorems and speaking English. The early 60s saw AI gaining popularity as evidenced by the generous fund provided by the US Department of Defense for AI research. The artificial research however met the doldrums in 1974 with funds on exploratory AI being cut off. The AI research was resuscitated in the early 80s with the commercial success of expert systems that applies knowledge and analytical skills of one or more human experts. By 1985 AI market reached the value of more than a billion dollars11. The AI market again fell into despair with the collapse of the Lisp Machine market in 198712. The highlight of AI success was in the 90s and early 21st century where it was widely used in the technology industry, providing the heavy lifting for logistics, data mining, medical diagnostics and many other areas13.
The general theory for AI is mainly based on several characteristics found in normal human being such as deduction, reasoning, problem solving, knowledge representation, planning, motion and manipulation, and perception, amongst others. When solving puzzles, playing board games or make logical deductions a normal human being would go through the process of conscious and step-by-step reasoning14. These traits were successfully imitated through algorithms developed by early AI researchers. Nonetheless, AI researchers have yet to unravel the methods of replicating human traits in solving problems using unconscious reasoning. In order for the machines to solve problems, it needs extensive knowledge about the world e.g. objects, properties, categories and relations between objects15; situations, events, states and time16; causes and effect17. Most knowledge is difficult to be represented due to 3 reasons; default reasoning and the qualification problem, McCarthy 18, unconscious knowledge and the breadth of common sense knowledge. In solving planning problems, the intelligent agent must have the ability of setting objective and achieving it19, thus it needs a way to visualize the future; i.e. having a representation of the state of the world and be able to make predictions about how their actions will change it. The