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Resources #1

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hugovk opened this issue Oct 3, 2018 · 10 comments
Open

Resources #1

hugovk opened this issue Oct 3, 2018 · 10 comments
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@hugovk
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@hugovk hugovk commented Oct 3, 2018

This is an open issue where you can comment and add resources that might come in handy for NaNoGenMo.

There are already a ton of resources on the old resources threads for the 2013 edition, the 2014 edition, the 2015 edition, the 2016 edition, and the 2017 edition.

@hugovk hugovk added the admin label Oct 3, 2018
@enkiv2
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@enkiv2 enkiv2 commented Oct 11, 2018

Our own @aparrish wrote Sea Duck, a system for generating tracery grammars out of rules about nouns, their properties, and the actions that can apply to them.

@enkiv2
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@enkiv2 enkiv2 commented Oct 17, 2018

Emily Short wrote a survey of recent academic work in narrative generation, some of which may be worth building on.

@korbonits
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@korbonits korbonits commented Oct 18, 2018

https://fiction.ict.usc.edu/creativehelp/ -- Melissa Roemmele presented about it in last year's NIPS Machine Learning for Creativity and Design workshop

@enkiv2
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@enkiv2 enkiv2 commented Oct 19, 2018

@ikarth
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@ikarth ikarth commented Oct 19, 2018

The alpha version of Expressionist is available: https://github.com/james-owen-ryan/expressionist

Expressionist is a tool for authoring interactive narrative text by James Ryan, Tyler Brothers, and others at UCSC. The documentation is a bit lacking at the moment, but it has some powerful abilities to generate context-specific text. James Ryan has also been researching the history of interactive and generated narrative, and has uncovered many interesting early projects, such as Grimes' Fairy Tales: A 1960s Story Generator a grammar-based narrative generator using our old friend Vladimir Propp.

@hugovk
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@hugovk hugovk commented Oct 21, 2018

I just published a new python package, being inspired by #procjam and #nanogenmo I created https://pypi.org/project/dragn/ which is my take on random.randint with more of a "Dice" interface.

https://twitter.com/lurst/status/1053561798530662401

@kleer001
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@kleer001 kleer001 commented Oct 25, 2018

What? Game dev convention videos that I've found inspiring. Why? Video games are entertainment, a book is ostensibly entertainment, they are inevitably going to be sharing attributes especially since we're sharing tools. How? With a grain of salt, not everything is going to apply, of course.

Magic: the Gathering: Twenty Years, Twenty Lessons Learned
https://www.youtube.com/watch?v=QHHg99hwQGY

Best practices for Procedural Narrative Generation:
https://www.youtube.com/watch?v=k2rgzZ2WXKo

Writing Modular Characters for System Driven Games:
https://www.youtube.com/watch?v=qX5-2D8SP5A

Tarn Adams - Villains in Dwarf Fortress
https://www.youtube.com/watch?v=4-7TtPX5uhg

The simplest Ai trick in the Book GDC 2015
https://www.youtube.com/watch?v=iVBCBcEANBc

Less is More: Designing Awesome Ai for Games
https://www.youtube.com/watch?v=1xWg54mdQos

The simplest Ai trick in the Book GDC 2013
https://www.gdcvault.com/play/1018059/The-Simplest-AI-Trick-in

PCG for everyone GDC 2017
https://www.youtube.com/watch?v=WumyfLEa6bU

The design of time GDC 2017
https://www.youtube.com/watch?v=gIrfxZ4KbOA&t=1532s

@cpressey
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@cpressey cpressey commented Oct 29, 2018

If you're working with sentence trees and you just want to see how a sentence might be parsed, you can paste it into the online Link Grammar Parser form at http://www.link.cs.cmu.edu/link/submit-sentence-4.html

(S (NP It)
   (VP was
       (NP a
           (ADJP dark and stormy)
           night))
   .)
(S (NP He)
   (VP wondered
       (SBAR (WHADVP why)
             (S (NP the night)
                (VP was
                    (ADJP (ADVP so)
                          dark and stormy)))))
   .)

There are other online forms which claim to also do this, but at the time I was looking into this, the Link Grammar one was the only one I found that actually worked.

The source code (actually a more recent version of it, with improvements; written in C, LGPL'ed) can be found here: https://github.com/opencog/link-grammar

@cpressey
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@cpressey cpressey commented Oct 29, 2018

Our own @aparrish wrote Sea Duck, a system for generating tracery grammars out of rules about nouns, their properties, and the actions that can apply to them.

In case you read this description and thought "oh cool, it compiles a description of a simulation to a Tracery grammar, how does that work?" (as I did, before I looked into it just now,) then you should know that that's not what it does. Rather, it runs a simulation, generating a list of events, and then renders those events by creating a Tracery grammar for each event, rendering it, and then immediately discarding it.

@hugovk
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@hugovk hugovk commented Oct 31, 2018

@ojahnn has created the oulipien NaNoLiPo for November, with 30 daily prompts/constraints to inspire [code to generate] creative writing:

https://github.com/ojahnn/NaNoLiPo2018

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