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RubyConf 2016 - Problem Solved! Using Logic Programming to Find Answers by Gavin McGimpsey We love Ruby's object orientation, and you might have heard functional programming is the new hotness. But don't leave home without one more paradigm! Logic programs express relations and constraints, allowing us to work with incomplete information, build knowledge systems, and find outputs of a system given whatever inputs are available. You'll see examples of logic programs using Ruby, learn about an algorithm that searches for a solution in a finite problem space, and explore potential applications for logic programming approaches, both in practical areas and for your mental models.
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In the video "Problem Solved! Using Logic Programming to Find Answers," Gavin McGimpsey introduces viewers to the concept and advantages of logic programming, particularly in the context of Ruby. He begins with his personal background, emphasizing his journey from law school test preparation to programming and problem-solving through logic. McGimpsey defines logic programming as a methodology that allows programmers to express relations and constraints, empowering them to solve problems with incomplete information. Throughout the talk, he highlights several vital concepts and examples: - **Introduction to Logic Programming:** The presentation introduces logic programming as a paradigm that originated from artificial intelligence, emphasizing its declarative nature, which allows users to specify what they want without detailing how to achieve it. - **Key Features of Logic Programming:** McGimpsey notes three primary characteristics: declarative programming (hiding underlying processes), expressing relationships between entities, and facilitating inference. - **Illustrative Examples:** He discusses the Atbash cipher to demonstrate declarative programming in Ruby, showing how it simplifies complex operations by focusing on the intended outcome rather than the operational details. - **Relational Thinking:** He contrasts functional thinking with relational thinking, using mathematics to explain how logic programming can reframe how problems are understood and solved. He employs SQL as an example of declarative relationships but points out its limitations in making inferences. - **Problem-Solving Strategies:** McGimpsey explains the N-Queens problem, showcasing various problem-solving strategies, including constraint propagation, depth-first search, and backtracking, alongside the Sudoku problem as a practical example of constraint processing. - **Logic Programming in Ruby:** He presents his development of a Ruby library for logic programming, named 'Russell,' which intends to make logic programming more accessible and embedded within Ruby, facilitating solutions to complex constraints. - **Applications of Logic Programming:** Examples are given, such as Prolog's use in expert systems and IBM's Watson, as well as creative applications like music generation through logic programming. In conclusion, McGimpsey encourages programmers to explore logic programming, experiment with writing logic-based solvers, and utilize existing libraries or create their own. He emphasizes the significance of understanding logic programming as a powerful approach to abstraction and problem-solving in programming.
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