HypeDyn is a procedural hypertext fiction authoring tool for non-programmers who want to create text-based interactive stories that adapt to reader choice. HypeDyn is free to download and open source, and runs on Linux, MacOS and Windows. You can download HypeDyn from http://www.partechgroup.org/hypedyn/download.html.

HypeDyn was written in Kawa Scheme, http://www.gnu.org/software/kawa/.

As part of our ongoing research, we are interested in how people use HypeDyn. Please let us know at hypedyn@partechgroup.org if you are using HypeDyn and would like to tell us about your experiences, in particular if you have made any changes to the code.

We are also interested in having authors take part in a more detailed study. If you are interested in helping with this study, please read the details at http://www.partechgroup.org/hypedyn/study.html.

Note that downloading/using HypeDyn does not require participation in the study.

1. Engagement (19/08/2010)
2. Traditional Asian games (Mahjong/麻將, mancala, etc.)
3. Rereading in interactive stories
4. Game design and movies
5. invite Shao Han to give a talk
6. ???

We also got side-tracked into discussing how to (eventually) change the playpod discussions into an “official” reading group, and the possibility of reviving the idea of bi-monthly movie screenings.

The description of the works is as follows:

FRAGMENTS: SELECTED STORIES FROM NM3222 INTERACTIVE STORYTELLING

“Closure is, as in any fiction, a suspect quality, although here it is made manifest. When the story no longer progresses, or when it cycles, or when you tire of the paths, the experience of reading ends… There is no simple way to say this.”
(Michael Joyce, afternoon: a story)

Fragments is a collection of short hypertext fictions written by students in NM3222 Interactive Storytelling. Created using the HypeDyn authoring tool, these works represent explorations of narrative, agency and play, investigating the nature of story and the role of the reader/writer in electronic literature.

- Stories –

1. Kow Wei Man, “No Turning Back”
2. Kua Yong Ern Shane, “Mirror, Mirror”
3. Kua Yong Ern Shane, “The Emperor’s Guide to the Galactic Empire”
4. Lye Zhi Le Gifford Justin, “Two Sides”
5. Ong Yit Sin, “The Last Click”
6. Rosmayati Tay Shieh Ting, “When one candle extinguishes”
7. Sooty Heng Ee Wen, “Voyage”

- HypeDyn implementation –

Alex Mitchell, Ruchi Bajoria and Zeng Qiang

One recent interesting development: we’ve started a games/interactive storytelling “discussion group”, hidden away in the CNM Playpod. Hopefully there will be many more interesting discussions like this one…

Why am I blogging about this?

It reminds me of the issues that come up in Facade regarding the balance between making choices clearly available and giving players an illusion of complete freedom.

I’ve been working on a gradual refinement of a simple story idea. In week 1 I started with a simple setting (a bus station), then fleshed that out to include some puzzles and player details in week 2, and an NPC (the bus driver) in week 3. For week 4, I’ll be adding new verbs, and (hopefully) reimplementing the entire story in Inform 7.

Thanks to Nick for posting about this at Grand Text Auto.

Why am I blogging about this?

My thesis revolves around creating tools and theories to help people write good interactive stories. The GAMBIT-funded research that Nick, Clara and I are working on is also looking at the relationship between platform and story in IF. So getting more direct hands-on experience authoring works in Inform should help give me more insight into the issues related to authoring interactive stories. And its fun…

The incorporation of the tool into Dreamweaver is also an advantage, as it allows authors who are already familiar with Dreamweaver to leverage their existing knowledge of the tool. However, from what I’ve seen of the tool, one major disadvantage is that there does not seem to be any support for visualization of the hypertext structure. I suspect that this will act as a barrier to adoption by novice authors.

The concepts behind Connection Muse are discussed in detail in this Hypertext 2000 paper.

Why am I blogging about this?

Conditional links and adaptive hypertext is one of the areas that I’ve been exploring in the Ariadne hypertext editor that I’ve been using for my interactive storytelling class. I’ve been interested in exploring the visualizations provided to the author, as my target users are generally novices. I’m also interested in the ways in which the tool affords thinking about storytelling. Conditional links and conditional text are an interesting boundary case between traditional hypertext and more procedurally generated interactive stories, and are an area which I’d like to explore in more detail.

“A reconstruction, in Common Lisp, of James Meehan’s program in _Inside_Computer_Understanding:_Five_Programs_Plus_Miniatures_ Roger Schank and Christopher Riesbeck (eds.)”

This is a very interesting early example of generative stories, based (almost entirely?) on character goals and whether or not a character trusts other characters.

Here’s a sample output, in this case under-specifying some of the variables (for example whether or not Joe and Irving trust each other.

CL-USER 219 > (micro-talespin-demo *story6*)

Once upon a time …
JOE WAS NEAR THE CAVE.
JOE KNEW THAT JOE WAS NEAR THE CAVE.
IRVING WAS NEAR THE OAK-TREE.
IRVING KNEW THAT IRVING WAS NEAR THE OAK-TREE.
JOE KNEW THAT IRVING WAS NEAR THE OAK-TREE.
THE WATER WAS NEAR THE RIVER.
JOE KNEW THAT THE WATER WAS NEAR THE RIVER.
THE HONEY WAS NEAR THE ELM-TREE.
IRVING KNEW THAT THE HONEY WAS NEAR THE ELM-TREE.
THE WORM WAS NEAR THE GROUND.
JOE KNEW THAT THE WORM WAS NEAR THE GROUND.
IRVING KNEW THAT JOE WAS NEAR THE CAVE.
THE FISH WAS NEAR THE RIVER.
IRVING KNEW THAT THE FISH WAS NEAR THE RIVER.
JOE THOUGHT THAT IRVING LIKED JOE.
JOE THOUGHT THAT IRVING DID NOT DOMINATE JOE.
One day,
JOE WAS HUNGRY .
JOE WANTED NOT TO BE HUNGRY .
JOE WANTED TO HAVE THE HONEY.
JOE WANTED TO KNOW WHERE THE HONEY WAS .
JOE WANTED IRVING TO TELL JOE WHERE THE HONEY WAS .
JOE THOUGHT THAT IRVING DECEIVED JOE.
[Y/N]?
>y

JOE WANTED IRVING TO THINK THAT IF IRVING WOULD NOT TELL JOE WHERE THE HONEY WAS THEN JOE WOULD STRIKE IRVING.
JOE WANTED TO BE NEAR IRVING.
JOE WENT TO THE OAK-TREE.
JOE WAS NEAR THE OAK-TREE.
JOE TOLD IRVING THAT IF IRVING WOULD NOT TELL JOE WHERE THE HONEY WAS THEN JOE WOULD STRIKE IRVING.
IRVING THOUGHT THAT JOE DECEIVED IRVING.
[Y/N]?
>y

JOE STRUCK IRVING.
IRVING WAS NOT ALIVE .
JOE THOUGHT THAT IRVING WOULD NOT TELL JOE WHERE THE HONEY WAS .
JOE THOUGHT THAT JOE DID NOT KNOW WHERE THE HONEY WAS .
JOE THOUGHT THAT JOE DID NOT HAVE THE HONEY.
JOE WANTED TO HAVE THE BERRIES.
JOE WANTED TO KNOW WHERE THE BERRIES WERE .
JOE THOUGHT THAT JOE DID NOT KNOW WHERE THE BERRIES WERE .
JOE THOUGHT THAT JOE DID NOT HAVE THE BERRIES.
JOE WANTED TO HAVE THE FISH.
JOE WANTED TO KNOW WHERE THE FISH WAS .
JOE THOUGHT THAT JOE DID NOT KNOW WHERE THE FISH WAS .
JOE THOUGHT THAT JOE DID NOT HAVE THE FISH.
JOE KNEW THAT JOE WAS HUNGRY .
The end.

Poor Joe. And the moral of the story? Perhaps that its better to trust people, especially if you’re a hungry bear?

The job of the author is to specify the various facts about the world, such as:

; Irving thinks that there are fish in the river
(irving (loc (actor fish) (val river))

As the story generator handles the characters’ negotiations and their attempts to reach their goals, if there are any facts that are not specified, the reader is asked to make a decision, which determines the fact. This blurs the roles of the reader and author – actually, they are doing the same thing, but at different stages. In the author’s case, the decisions are make during the writing process, whereas for the reader the decisions are made while reading the story, but the types of decisions, in this case, are exactly the same.

Why am I blogging about this?
(Note: I’m stealing this format from Pasta and Vinegar)

Although the stories are very simplistic, Micro-Talespin is a very compelling demonstration of what can be done with automatic story generation. This is one of possible many paths down which research into interactive storytelling could lead. Even if I do end up avoiding going too deeply into AI, I should at least understand the issues involved in this type of system.

I’m also thinking of including a generative story assignment in my Interactive Storytelling class this coming semester, inspired by what I’ve read about Mike Mateas’s use of Wide Ruled.