The first systematic study of parallelism in computation by two pioneers in the field.Reissue of the 1988 Expanded Edition with a new foreword by Leon BottouIn 1969, ten years after the discovery of the perceptron-which showed that a machine could be taught to perform certain tasks using examples-Marvin Minsky and Seymour Papert published Perceptrons, their analysis of the computational capabilities of perceptrons for specific tasks. As Leon Bottou writes in his foreword to this edition, "e;Their rigorous work and brilliant technique does not make the perceptron look very good."e; Perhaps as a result, research turned away from the perceptron. Then the pendulum swung back, and machine learning became the fastest-growing field in computer science. Minsky and Papert's insistence on its theoretical foundations is newly relevant.Perceptrons-the first systematic study of parallelism in computation-marked a historic turn in artificial intelligence, returning to the idea that intelligence might emerge from the activity of networks of neuron-like entities. Minsky and Papert provided mathematical analysis that showed the limitations of a class of computing machines that could be considered as models of the brain. Minsky and Papert added a new chapter in 1987 in which they discuss the state of parallel computers, and note a central theoretical challenge: reaching a deeper understanding of how "e;objects"e; or "e;agents"e; with individuality can emerge in a network. Progress in this area would link connectionism with what the authors have called "e;society theories of mind."e;

The first systematic study of parallelism in computation by two pioneers in the field.Reissue of the 1988 Expanded Edition with a new foreword by Leon BottouIn 1969, ten years after the discovery of the perceptron-which showed that a machine could be taught to perform certain tasks using examples-Marvin Minsky and Seymour Papert published Perceptrons, their analysis of the computational capabilities of perceptrons for specific tasks. As Leon Bottou writes in his foreword to this edition, "e;Their rigorous work and brilliant technique does not make the perceptron look very good."e; Perhaps as a result, research turned away from the perceptron. Then the pendulum swung back, and machine learning became the fastest-growing field in computer science. Minsky and Papert's insistence on its theoretical foundations is newly relevant.Perceptrons-the first systematic study of parallelism in computation-marked a historic turn in artificial intelligence, returning to the idea that intelligence might emerge from the activity of networks of neuron-like entities. Minsky and Papert provided mathematical analysis that showed the limitations of a class of computing machines that could be considered as models of the brain. Minsky and Papert added a new chapter in 1987 in which they discuss the state of parallel computers, and note a central theoretical challenge: reaching a deeper understanding of how "e;objects"e; or "e;agents"e; with individuality can emerge in a network. Progress in this area would link connectionism with what the authors have called "e;society theories of mind."e;