Special Issue on Logic-Based Artificial Intelligence.

Since its inception, research in the field of I Artificial Intelligence i (AI) has had a fundamentally logical approach; therefore, discussions have taken place to establish a way of distinguishing symbolic AI from sub-symbolic AI, basing the approach instead on the statistical approaches typical of I machine learning i , I deep learning i or I Bayesian networks i . Hence, the problem is solved by forcing the following to be false: there is an edge from node I X i to node I Y i , such that I X i is colored by the same color of I Y i (named I Z i in the rule): HT <math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo><-</mo><mi>e</mi><mi>d</mi><mi>g</mi><mi>e</mi><mo>(</mo><mi>X</mi><mo>,</mo><mi>Y</mi><mo>)</mo><mo>,</mo><mspace width="4pt" /><mi>c</mi><mi>o</mi><mi>l</mi><mi>o</mi><mi>r</mi><mi>e</mi><mi>d</mi><mo>(</mo><mi>X</mi><mo>,</mo><mi>Z</mi><mo>)</mo><mo>,</mo><mspace width="4pt" /><mi>c</mi><mi>o</mi><mi>l</mi><mi>o</mi><mi>r</mi><mi>e</mi><mi>d</mi><mo>(</mo><mi>Y</mi><mo>,</mo><mi>Z</mi><mo>)</mo><mo>.</mo></mrow></semantics></math> ht These two rules allow us to encode the result in a sound and complete the 3-coloring problem, also offering, thanks to the symbolic approach, an almost immediate understanding for a human being of the meaning encoded in the rules. [Extracted from the article]