Abstract
Artificial intelligence (AI) was born connectionist when in 1943 Warren S. McCulloch and Walter Pitts introduced the first sequential logic model of neuron. The 1950s sees the passage from numerical to symbolic computation with the christening of AI in 1956. In 1986, there is a rebirth of connectionism at the same time that an emphasis in knowledge modeling and inference, both symbolic and connectionist. We thus reach the present state in which different paradigms coexist (symbolic, connectionist, situated and hybrid). In this work, we will attempt (1) to approach the concept of AI both as a science of the natural and as knowledge engineering (KE); (2) summarize some of the conceptual, formal and methodological approaches to the development of AI during the last 50 years, (3) mention some of the constitutive differences between human knowing and machine knowing and (4) propose some suggestions that we believe must be adopted to progress in developing AI.
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