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The Quest for Efficient Boolean Satisfiability Solvers | SpringerLink
The Quest for Efficient Boolean Satisfiability Solvers | SpringerLink

... rather we focus on techniques with consistent demonstrated efficiency in available solvers. For the most part, we focus on techniques within the basic DPLL search framework, but also briefly describe other approaches and look at some possible future research directions. ...
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No Slide Title
No Slide Title

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BCA-601
BCA-601

... The last unit is devoted to natural language processing, syntactic processing, semantic analysis, discourse and pragmatic processing and conversational postulates. The book follows the self-instructional mode wherein each Unit begins with an Introduction to the topic. The Unit Objectives are then ou ...
Intelligent Agents: Theory and Practice
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Genetic Programming - School of Computer Science and Electronic
Genetic Programming - School of Computer Science and Electronic

... • Reproduction: Copy the selected individual program into the new population. • Crossover: Create new offspring program(s) for the new population by recombining randomly chosen parts from two selected programs. • Mutation: Create one new offspring program for the new population by randomly mutating ...
Artificial Intelligence
Artificial Intelligence

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6.034 Artificial Intelligence. Copyright © 2004 by Massachusetts
6.034 Artificial Intelligence. Copyright © 2004 by Massachusetts

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Automatic Genre-Dependent Composition using Answer Set
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Learning logical definitions from relations

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What are Expert Systems?
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X is A - Wiki Index
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Computing Preferred Answer Sets by Meta
Computing Preferred Answer Sets by Meta

... ASP meta-interpreters, on the other hand, are formulated in a truly declarative way. This is more amenable to realizing interpreters for KR languages which have a purely declarative reading, and where syntactic elements such as the order of rules, or the order of literals in the body of a rule are n ...
Lecture 1: Getting Started With Python
Lecture 1: Getting Started With Python

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Description Logics
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Discriminative Structure and Parameter Learning for Markov
Discriminative Structure and Parameter Learning for Markov

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Scholarly Interest Report
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Chapter 1: Introduction to Expert Systems
Chapter 1: Introduction to Expert Systems

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Systematic Verification of the Modal Logic Cube in Isabelle
Systematic Verification of the Modal Logic Cube in Isabelle

... given for the equivalences of different axiomatizations and the inclusion relations shown in the cube. Our solution makes extensive use of the fact that all modal logics found in the cube are sound and complete because they arise from base modal logic K by adding Sahlqvist axioms. This is in contras ...
Reasoned Use of Expertise in Argumentation
Reasoned Use of Expertise in Argumentation

... authority to influence opinion in argumentation is commonplace, and worth guarding against. But does this suggest that all appeals to expert authority in argument are fallacious? It should not. For taking into account the intelligent and informed opinion of a legitimate expert on a question that one ...
Applications of Preferences using Answer Set Programming
Applications of Preferences using Answer Set Programming

... Key words: Preferences, Answer Set Programming, Ordered Disjunction Programs, Planning. ...
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Logic programming

Logic programming is a programming paradigm based on formal logic. A program written in a logic programming language is a set of sentences in logical form, expressing facts and rules about some problem domain. Major logic programming language families include Prolog, Answer set programming (ASP) and Datalog. In all of these languages, rules are written in the form of clauses:H :- B1, …, Bn.and are read declaratively as logical implications:H if B1 and … and Bn.H is called the head of the rule and B1, …, Bn is called the body. Facts are rules that have no body, and are written in the simplified form:H.In the simplest case in which H, B1, …, Bn are all atomic formulae, these clauses are called definite clauses or Horn clauses. However, there exist many extensions of this simple case, the most important one being the case in which conditions in the body of a clause can also be negations of atomic formulae. Logic programming languages that include this extension have the knowledge representation capabilities of a non-monotonic logic.In ASP and Datalog, logic programs have only a declarative reading, and their execution is performed by means of a proof procedure or model generator whose behaviour is not meant to be under the control of the programmer. However, in the Prolog family of languages, logic programs also have a procedural interpretation as goal-reduction procedures:to solve H, solve B1, and ... and solve Bn.Consider, for example, the following clause:fallible(X) :- human(X).based on an example used by Terry Winograd to illustrate the programming language Planner. As a clause in a logic program, it can be used both as a procedure to test whether X is fallible by testing whether X is human, and as a procedure to find an X that is fallible by finding an X that is human. Even facts have a procedural interpretation. For example, the clause:human(socrates).can be used both as a procedure to show that socrates is human, and as a procedure to find an X that is human by ""assigning"" socrates to X.The declarative reading of logic programs can be used by a programmer to verify their correctness. Moreover, logic-based program transformation techniques can also be used to transform logic programs into logically equivalent programs that are more efficient. In the Prolog family of logic programming languages, the programmer can also use the known problem-solving behaviour of the execution mechanism to improve the efficiency of programs.
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