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The Logic Programming podcast. About the history, future, and wider landscape of Logic Programming.

The Search Space Felix Holmgren

    • Teknologi
    • 5,0 • 4 betyg

The Logic Programming podcast. About the history, future, and wider landscape of Logic Programming.

    #6 - Adam Smith on Answer Set Programming

    #6 - Adam Smith on Answer Set Programming

    Adam Smith talks about Answer Set Programming, and how he's used it in game design and other areas.
    Visit the show's web page: thesearch.space
    Show notes
    | Torsten Schaub at Potsdam University
    Several of his presentations contain the formula
    ASP = DB + LP + KR + SMT^n
    ASP: Answer Set ProgrammingDB: DatabaseLP: Logic ProgrammingKR: Knowledge RepresentationSMT: SAT Modulo Theories
    SAT solver: Boolean Satisfiability
    | this refraction game that I had made a puzzle generator for
    Described in Adam's dissertation.
    | the Potassco tools from University of Potsdam.
    potassco.org
    | A book called Procedural Content Generation in Games
    www.pcgbook.com
    | There's this idea due to Kate Compton ... of the 10 000 bowls of oatmeal problem
    http://www.galaxykate.com/blog/generator.html
    | We modeled a design space of information visualizations, line plots and scatter plots and bar charts
    "Formalizing Visualization Design Knowledge as Constraints: Actionable and Extensible Models in Draco"| a Python library called Clorm .. so that you can define your problem instances with Python objects
    github.com/potassco/clorm
    | the concept of elaboration tolerance that when someone gives you some clarification about how your domain works, can you incorporate that change by just adding more code to add more choices or more constraints?
    John McCarthy's paper on elaboration tolerance
    | a paper from Google DeepMind ... describing a system called the Apperception Engine
    "Making sense of sensory input", Evans et al
    | taught a class called Applied ASP a few years ago
    Lecture slides, programming assignments, reading assignments here: canvas.ucsc.edu/courses/1338
    | Once you want to write a program that's more than 30 lines long, how do you profile it? How do you test it? How do you deploy it?
    Slides from a talk about Adam's test automation framework: Unit Test Automation for ASP with Ansunit
    Try ASP from your browser: https://potassco.org/clingo/run/


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    • 1 tim. 13 min
    #5 - Kevin Feeney on TerminusDb and the Semantic Web

    #5 - Kevin Feeney on TerminusDb and the Semantic Web

    Kevin Feeney talks about different kinds of graph databases, the role of logic in the Semantic Web vision, the shortcomings the technologies created to fulfill that vision, and how TerminusDb, the database project Kevin co-founded, is seeking to finally make good on the promise of the Semantic Web.

    • 1 tim. 27 min
    #4 - Markus Triska on constraints and the power of Prolog

    #4 - Markus Triska on constraints and the power of Prolog

    Markus Triska talks about his work on Constraint Logic Programming packages, writing robust software, modern features of Prolog systems, and the future of logic programming.

    • 1 tim. 5 min
    #3 - Chris Martens on narrative generation

    #3 - Chris Martens on narrative generation

    Chris Martens talks about using linear logic programming to generate interactive narratives, and various ways to apply logic to games and digital arts.

    • 1 tim.
    #2 - Ryan Brush on retaking rules for developers

    #2 - Ryan Brush on retaking rules for developers

    Ryan Brush talks about Clara, a rules engine written in Clojure, and how to close the semantic gap between specification and implementation.

    • 49 min
    #1 - The Poet of Logic Programming

    #1 - The Poet of Logic Programming

    An interview with Robert Kowalski, the co-creator of the field of logic programming and of the language Prolog. The conversation ranges over the history of Prolog, the ill-famed Fifth Generation Computer Systems project, the relation between symbolic AI and connectionist AI including deep learning, why rule engines fail at logic, and the future of logic programming. Find show notes and more on thesearch.space, and follow the show on Twitter: @searchspacepod

    • 1 tim. 35 min

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