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Logic programming is a programming, database and knowledge representation paradigm based on formal logic. A logic program is a set of sentences in logical form, representing knowledge about some problem domain. Computation is performed by applying logical reasoning to that knowledge, to solve problems in the domain.
A level shifter connects one digital circuit that uses one logic level to another digital circuit that uses another logic level. Often two level shifters are used, one at each system: A line driver converts from internal logic levels to standard interface line levels; a line receiver converts from interface levels to internal voltage levels.
The left figure below shows a binary decision tree (the reduction rules are not applied), and a truth table, each representing the function (,,).In the tree on the left, the value of the function can be determined for a given variable assignment by following a path down the graph to a terminal.
Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...
The physical level describes complex low-level data structures in detail. Logical level – The next higher level of abstraction describes what data the database stores, and what relationships exist among those data. The logical level thus describes an entire database in terms of a small number of relatively simple structures.
Constraint logic programming is a form of constraint programming, in which logic programming is extended to include concepts from constraint satisfaction. A constraint logic program is a logic program that contains constraints in the body of clauses. An example of a clause including a constraint is A (X, Y):-X + Y > 0, B (X), C (Y).
Abductive logic programming (ALP) is a high-level knowledge-representation framework that can be used to solve problems declaratively, based on abductive reasoning. It extends normal logic programming by allowing some predicates to be incompletely defined, declared as abducible predicates.
Given a goal clause, represented as the negation of a problem to be solved : with selected literal , and an input definite clause: . whose positive literal (atom) unifies with the atom of the selected literal , SLD resolution derives another goal clause, in which the selected literal is replaced by the negative literals of the input clause and the unifying substitution is applied: