Skip to Main Content
Since Alan Turing, computer scientists have been interested in understanding natural intelligence by reproducing it in machine form. The field of artificial intelligence is characterized, to a large extent, by search algorithms. As search is a computational process, this too has been well studied as part of theoretical computer science, leading to famous results on the computational hardness of problems. This chapter provides an overview of why most search problems are known to be hard and why general search strategies are impossible. It then discusses various heuristic approaches to computational search. The fundamental message intended is that any intelligent system of sufficient complexity, using search to guide its behavior, should be expected to find solutions that are good enough, rather than the best. In other words, it is argued that natural and artificial brains should satisfice rather than optimize.