Dorian Passer's ParserComp 2022 Reviews

Hi there!

I developed a new model — a mountain of fun — that I’d like to test out on ParserComp 2022.


I’ve never been good at playing IF — even though eventually through programming, I found that I actually did have a knack for problem solving. So instead of writing a more traditional review, I’d like to share my read-through experiences in terms of this new model (that has a silly name). Even though I’m not writing a traditional review, I’ll still use the term review to keep it simple.

Here’s what I do for each read-through:

  • Use the PR-IF Cheat Sheet.
  • Don’t ask for outside help.
  • Stop reading after one contiguous delay of 15 minutes.*
    (*Potential maximum delay across all works this year is 4 hours and 30 minutes.)

My writings about IF are not very good either, so please take my attempts as they are — the opinions of an uninformed beginner. I’m definitely not trying to pass judgement to anyone. I deeply appreciate all the effort that went into authoring these works. Thank you for bringing your work to ParserComp so that we can all have fun this summer!


Here’s what you can expect about the format that I use for each review.

  • title
    • author
  • summary
    • brief experience
  • a mountain of fun
    • defined for convenience
  • discussion
    • areas of the mountain
  • conclusion
    • final steps

What is a Mountain of Fun?

I use Barrett’s concepts of an allostatic-interoceptive brain to inspire a new model of fun, which I’m calling the mountain of fun. In a nutshell, this model compares and contrasts past and present experiences. But please keep in mind that since variation is the norm with people, there is a degree of subjectivity when using this model to describe one’s experience.

Brain too little just right too much
Sensory Input blocked focused unfiltered
Predictions offline online overloaded

blocked or offline = too many similarities to past experiences = UNDERWHELM
unfiltered or overloaded = too many differences from past experiences = OVERWHELM
focused or online = manageable amount of differences or similarities from past experiences = FUN

Sensory Input Prediction Past Experiences Phenomenon Mountain
1 too little too little blocked, offline UNDERWHELM foot
2 too little too much blocked, overloaded UNDERWHELM-OVERWHELM slope
3 too little just right blocked, online UNDERWHELM-FUN mesa
4 just right too little focused, offline FUN-UNDERWHELM mesa
5 just right just right focused, online FUN (a.k.a. learning) peak
6 just right too much focused, overloaded FUN-OVERWHELM mesa
7 too much just right unfiltered, online OVERWHELM-FUN mesa
8 too much too little unfiltered, offline OVERWHELM-UNDERWHELM slope
9 too much too much unfiltered, overloaded OVERWHELM foot

Area 1 and Area 9 are moments that are not fun.
Area 2 and Area 8 are moments that just pass the time.
Area 3 and Area 4 are fun moments that eventually become underwhelming.
Area 6 and Area 7 are fun moments that eventually become overwhelming.
Area 5 are moments that are fun!


I use the mountain of fun to share how I either maintain enough momentum to reach the finish line or sputter out after too many delays.

I end each review by detailing the state of my read-through after I was done reading. Then I thank the author and say goodbye!


Hopefully, you’ll find something interesting in this model.

And thank you so much for your time again!

[EDIT 1: Clarified that the 15 minute delay is 15 contiguous minutes, and not just several shorter delays that add up to 15 minutes.]

[EDIT 2: Change mountain region of Area 3, Area 4, Area 6, and Area 7 from slope to mesa.]

4 Likes

Thinking on it, this picture has more sense in Spanish, where we call roller-coaster “Russian Mountains” ¬.¬

3 Likes

Euripides Enigma

By Larry Horsfield

Summary

After bumbling around a damaged facility, slowly making my way through darkened corridors, I get separated from my squad, and then I eventually become stuck in a control room. No one hears my screams for help.

Mountain of Fun Recap

What is a Mountain of Fun?

I use Barrett’s concepts of an allostatic-interoceptive brain to inspire a new model of fun, which I’m calling the mountain of fun. In a nutshell, this model compares and contrasts past and present experiences. But please keep in mind that since variation is the norm with people, there is a degree of subjectivity when using this model to describe one’s experience.

Brain too little just right too much
Sensory Input blocked focused unfiltered
Predictions offline online overloaded

blocked or offline = too many similarities to past experiences = UNDERWHELM
unfiltered or overloaded = too many differences from past experiences = OVERWHELM
focused or online = manageable amount of differences or similarities from past experiences = FUN

Sensory Input Prediction Past Experiences Phenomenon Mountain
1 too little too little blocked, offline UNDERWHELM foot
2 too little too much blocked, overloaded UNDERWHELM-OVERWHELM slope
3 too little just right blocked, online UNDERWHELM-FUN slope
4 just right too little focused, offline FUN-UNDERWHELM slope
5 just right just right focused, online FUN (a.k.a. learning) peak
6 just right too much focused, overloaded FUN-OVERWHELM slope
7 too much just right unfiltered, online OVERWHELM-FUN slope
8 too much too little unfiltered, offline OVERWHELM-UNDERWHELM slope
9 too much too much unfiltered, overloaded OVERWHELM foot

Area 1 and Area 9 are moments that are not fun.
Area 2 and Area 8 are moments that just pass the time.
Area 3 and Area 4 are fun moments that eventually become underwhelming.
Area 6 and Area 7 are fun moments that eventually become overwhelming.
Area 5 are moments that are fun!

Discussion

Maybe it’s because I haven’t read the previous chapters, but I didn’t find myself draw in at the beginning. The hints from Zen helped to suspend my disbelief. I was bummed when I was separated from Zen and could no longer seek his assistance.

The VOCAB command was very helpful! But I was soon overwhelmed scanning over the list of commands every time I ran into a delay, which for me was frequent. I found myself experiencing a mix of both sensory overload and prediction overload. I take the blame for this due to my inexperience with the genre.

I feel like the sparse descriptions didn’t give me enough sensory information to nudge me in the right direction. I examined the electronic components and the trays, but I didn’t know how to find or take a spare switch with me. Again, I take the blame for this.

I think I’d place my general experience near the bottom slope of the mountain, around Area 2 and Area 8, but there were a few moments I felt that I was in Area 3.

Conclusion

I got stuck around the control room and couldn’t figure out how to repair the ESCC switch with the electronic components from the storeroom.


Many thanks to Larry Horsfield for making Euripides Enigma and congratulations for being part of ParserComp 2022!!

3 Likes

When you talk about “this model compares and contrasts past and present experiences”, I suppose you mean how your game play evolves trough time during the same game comparing current state and fun feeling of your play with the ones just one moment before. Am I right? (This is what I have understood from “allostatic”, and your comment about “maintain enough momentum to reach the finish”).

I’m not very sure what is the meaning of the brain column:

Sensory Input: Is this what are you currently “seeing” of “feeling” playing the game?

Predictions: Is this how you expect the game will evolve from the current situation, like “oh, this will be boring”, o “oh, you will see how cool and original is this and the butler will be unexpectedly the assassin!”? Perhaps something related with perceived objectives and feeling of “being lost”?

Or am I the one completely lost here? ¬.¬

You also talk about the “delays”, being these enemies of the Joy. Are they real time delays due to not finding what to do or not finding the solution, for example, or do they refer to something else?

I have made this graphic (not sure if your mountain would be something like this):

If I am correct, your gameplay sessions would consist in a series of values of the lower axis of this graphics, reflecting your feelings in that moment related with previous movements and expectations on future, with for example one value each minute, giving something like this for a 13 minutes session, for example:

START: 1 5 5 3 2 3 5 8 8 9 5 3 5 : END

This values would be used to calculate some average value to obtain a final “star rate” for the game.

Or I completely misunderstood the method?

1 Like

Thank for the insightful comments, AZ!

I think that you understand everything for the most part! But please let me clarify some bits for myself.


So the term “experience” covers how an audience thinks about both the stateful and stateless mechanics of a work. So you are right to intuit this here, and you are right again to think that an audience would compare their “past experiences” over time. However, “past experiences” refers to all past experiences, not just the immediate prior experience. This topic is related to “delays”, which I discuss soon.


Looks like you understand what I mean by sensory input and predictions, especially with what “experience” means in stateless and stateful media. I think some more details about Barrett’s concepts would be helpful now.

Barrett’s brain concept takes an embodied approach. What this means for literature is that if an audience reads about sensory information, that’s enough to cause their brain to start making predictions. For Barrett’s concepts, sensory input and predictions are two sides of the same coin. My interpretation is that there is a “sweet spot” of sensory input and predictions where an audience feels like their experience is “just right”.


The term “delay” pretty much means anything that has the potential to stop an audience’s suspension of disbelief. With stateful media, that could be a dumb puzzle or program bug or a million other things. With stateless media, that could be bad spelling/style/grammar or bad plotting or a million other things. But not all delays are bad! In fact, delays are an essential element of an experience, especially within both games and literature. With stateful media, that could be a brilliant puzzle, or with stateless media, that could be a masterful pace through a plot. But since variation is the norm with an audience, figuring out when, where, how, and why to time those delays is incredibly difficult.


I’m not sure about this graph because the “areas” of the mountain are nominal data points (which means that the areas are labels and not numbers). And an audience can use more than one data point at a moment in time. Maybe the nominal data graph would look like some sort of bar chart? Like something in these piano programs with the falling blocks?

mountain_graph_concept

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1 Like

October 31st.

By Finn Rosenløv

Summary

On the outskirt of town on All Hollows’ Eve, I wander the grounds of an old manor, slowly learning about the grim history of its inhabitants. Then all of a sudden, before even entering the mansion, I receive a fright so terrible that I cease to exist!

Mountain of Fun

What is a Mountain of Fun?

I use Barrett’s concepts of an allostatic-interoceptive brain to inspire a new model of fun, which I’m calling the mountain of fun. In a nutshell, this model compares and contrasts past and present experiences. But please keep in mind that since variation is the norm with people, there is a degree of subjectivity when using this model to describe one’s experience.

Brain too little just right too much
Sensory Input blocked focused unfiltered
Predictions offline online overloaded

blocked or offline = too many similarities to past experiences = UNDERWHELM
unfiltered or overloaded = too many differences from past experiences = OVERWHELM
focused or online = manageable amount of differences or similarities from past experiences = FUN

Sensory Input Prediction Past Experiences Phenomenon Mountain
1 too little too little blocked, offline UNDERWHELM foot
2 too little too much blocked, overloaded UNDERWHELM-OVERWHELM slope
3 too little just right blocked, online UNDERWHELM-FUN slope
4 just right too little focused, offline FUN-UNDERWHELM slope
5 just right just right focused, online FUN (a.k.a. learning) peak
6 just right too much focused, overloaded FUN-OVERWHELM slope
7 too much just right unfiltered, online OVERWHELM-FUN slope
8 too much too little unfiltered, offline OVERWHELM-UNDERWHELM slope
9 too much too much unfiltered, overloaded OVERWHELM foot

Area 1 and Area 9 are moments that are not fun.
Area 2 and Area 8 are moments that just pass the time.
Area 3 and Area 4 are fun moments that eventually become underwhelming.
Area 6 and Area 7 are fun moments that eventually become overwhelming.
Area 5 are moments that are fun!

Discussion

The introduction got me into a state of suspended disbelief. I was ready to walk through those manor gates to start exploring that spooky old mansion!


I liked the input’s autocomplete feature because it reduced delays for me. I don’t remember seeing this feature in Horsfield’s Euripides Enigma, but I played that game in a browser, so I don’t know if that made a difference.


The integrated hints kept my momentum going. For example, when I tried to talk to ghost in the garden, the system mapped my expectations to the affordances of the system. These integrated hints, combined with the author’s prose, gave me just enough sensory input as to not overload my predictions. For these moments, I feel that I am at the peak of the mountain at Area 5. I’m having fun!


Eventually, my inexperience with the genre’s conventions causes delays to occur more frequently, and I begin to seek more guidance from the comprehensive menu-driven hint system. To me, this hint system seemed like a metaleptic character that took a conversational approach to gradually reveal its hints. It’s well implemented! (And I can’t help but think how it reminds me of my own approach to stateful media.) However, the hint system has a multi-step process to exit the system, and this process fast becomes tedious to execute; I find myself slipping down the slope into Area 4. Because this is mostly due to my inexperience, I’ll take the blame for this.


Finally, Windows 11 cuts short my reading time after Windows Security deletes the executable for the game.

Conclusion

I stopped after Windows Security on Windows 11 flagged and quarantined the game executable as a virus. Even though I presume this is a false positive, I was scared enough to stop. Unfortunately, I don’t think I’m going to play anymore non-browser-based games for these competitions. Here’s a screenshot of the alert:


Despite this final surprise, I was enjoying my time around the manor grounds while it lasted.


Many thanks to Finn Rosenløv for making Oct 31st. and congratulations for being part of ParserComp 2022!!

This is unfortunately a known problem with ADRIFT 5 that seems to come and go over time as virus definition databases are updated. No one is really sure what causes it. You could try using a different interpreter (shameless self-promotion here :wink:) to run the .blorb version of the game that is also offered for download.

2 Likes

Whew :relieved: Thanks for letting me know this a common thing.

And awesome work on writing an interpreter! That is so cool!

2 Likes

I forgot to mention this earlier, but I love these graphs that you’re making! Thank you!


I see what you were trying to do with this version, but I think it misses some insights that I discovered from this model. Let me provide a bit more context to help ourselves here.


When I used to visualize a range of fun, “not fun” was at one end of the range, and “fun” was at the other. For me, fun and not fun were self-apparent; in other words, it wasn’t very hard for me to make a black-and-white determination between fun and not fun. That dark chasm between fun and not fun was what left me scratching my head in confusion.

The chasm between fun and not fun was a big problem to me. So I applied a classic problem solving technique — break up something big into a bunch of smaller pieces. Using Barrett’s concepts, I enumerated all the states between {sensory input, prediction} and {too little, just right, too much} and then placed them along a line. This is when I discovered two types of “not fun” and two ranges between “fun” and “not fun”. So exciting!

With the mountain of fun, I found a reasonable explanation for the transition between fun and not fun. I call this transition the “slope of the mountain”. The slope is still a bit mysterious to me. For instance, Area 2 is (reasonably) the bottom of a slope. But Area 3 is (simply) the opposite of Area 4; are these two opposite areas equal to one another, or is one better than the other? [Note: I now label these two areas as the mesa.] I have this same concern with both slopes; are these two slopes equal to each other, or is one slope “less fun”?


I hope now you see why I’m bad at making a graph of the mountain of fun. However, it’s a fun exercise, so here’s a (notional) graph that envisions a “mesa” surrounding the peak, where the mesa reflects an assumed equality between Area 3 and 4 and Area 6 and 7.

(I re-implemented your graph in Google Slides :partying_face: )

1 Like

The Muse

By Xavier Carrascosa

Summary

I couldn’t take any more. Would my pleas be heard to awaken from this nightmare?

Mountain of Fun

What is a Mountain of Fun?

I use Barrett’s concepts of an allostatic-interoceptive brain to inspire a new model of fun, which I’m calling the mountain of fun. In a nutshell, this model compares and contrasts past and present experiences. But please keep in mind that since variation is the norm with people, there is a degree of subjectivity when using this model to describe one’s experience.

Brain too little just right too much
Sensory Input blocked focused unfiltered
Predictions offline online overloaded

blocked or offline = too many similarities to past experiences = UNDERWHELM
unfiltered or overloaded = too many differences from past experiences = OVERWHELM
focused or online = manageable amount of differences or similarities from past experiences = FUN

Sensory Input Prediction Past Experiences Phenomenon Mountain
1 too little too little blocked, offline UNDERWHELM foot
2 too little too much blocked, overloaded UNDERWHELM-OVERWHELM slope
3 too little just right blocked, online UNDERWHELM-FUN slope
4 just right too little focused, offline FUN-UNDERWHELM slope
5 just right just right focused, online FUN (a.k.a. learning) peak
6 just right too much focused, overloaded FUN-OVERWHELM slope
7 too much just right unfiltered, online OVERWHELM-FUN slope
8 too much too little unfiltered, offline OVERWHELM-UNDERWHELM slope
9 too much too much unfiltered, overloaded OVERWHELM foot

Area 1 and Area 9 are moments that are not fun.
Area 2 and Area 8 are moments that just pass the time.
Area 3 and Area 4 are fun moments that eventually become underwhelming.
Area 6 and Area 7 are fun moments that eventually become overwhelming.
Area 5 are moments that are fun!

Discussion

The art and prose work together to suspend my disbelief, though I feel like the art is doing more of the work here.


I like how the instructions are brief and easy to remember. Get stuck? Type Help. Which I do and I’m so glad I did. The help section is very well put together, covering topics up from the macro level down to the micro level. This really helps me to compartmentalize information.

Since the help section is so, well, helpful, I read it all. I’m learning here, and to me, this is fun! Thanks for making sure I understand the conventions of the genre.


I’m taking a tangent here, but I’d like to comment on some passages from the help section.

Make sure you’ve exhausted all the options in your environment […] Reread. Look back at things you’ve already looked at. Sometimes this will trigger an idea you hadn’t thought of.

This reminds me of a pixel hunt. For me, this causes me to make many predictions, which feels overwhelming, yet at the same time, this process provides dwindling sensory input, which feels underwhelming. This flow usually puts me at the bottom of the northern slope around Area 2 of the mountain.

Anyways, I’ll get back to the review now.


I pick up the quill and write in the book. Then an exhaustive (and exhausting) examination of the room leads me to examine muse. Progress continues as I look forward to venturing away from Area 2.


Now I reach a delay while I search a sentence to find the next verb to use. In a way, this feels like clicking a hyperlink — a hidden hyperlink. For me, this “hidden” mechanism of parser-based works — with “hidden choice lists” and “hidden hyperlinks” — makes for a frustrating climb up the northern slope of the mountain.

But so far in this work, the “hidden hyperlinks” seem to be singular and apparent, which makes them feel just right.


Soon, I complete the first act. And without looking at the hint system too much or doing too many rote environmental manipulations. I’m excited to keep this momentum going until the final act.

For the most part, my delays seem to be happening at a good pace. With terse prose and evocative illustrations, my sensory input feels on the cusp of just right; telegraphed prose and an apparent interaction pattern helps to scope down my prediction space, making this feel just right, too. Here I’m mostly around the upper mesa of the mountain, with moments of summiting. I’m liking where I’m at!


But soon, I’m back to exhausting many verb-noun pairs on the environment. My delay builds up and my suspension of disbelief goes down. I’m moving towards the bottom of the northern slope near the foot of the mountain.

I don’t know what else to do, so I consult the hints. After I decipher the not-so-subtle hint, I’m disappointed. I feel like this act on lust would benefit from a different topic, like a cheating spouse.

Thankfully, I remember that I’m a prisoner, so I try to beg the muse to stop. It works and I find myself at an end.

Conclusion

This is only my biased opinion, but since this work deemphasizes geographical exploration, I would have been fine if the prose was more “literary” and less “utilitary”.

Overall (and besides having an obvious lapse in taste), The Muse is an effective work in terms of momentum and suspension of disbelief.


Many thanks to Xavier Carrascosa for making The Muse and congratulations for being part of ParserComp 2022!!

You Won’t Get Her Back

By Andrew Schultz

Summary

I could not get her back, even with the sheer force of my brute strength.

Mountain of Fun

What is a Mountain of Fun?

I use Barrett’s concepts of an allostatic-interoceptive brain to inspire a new model of fun, which I’m calling the mountain of fun. In a nutshell, this model compares and contrasts past and present experiences. But please keep in mind that since variation is the norm with people, there is a degree of subjectivity when using this model to describe one’s experience.

Brain too little just right too much
Sensory Input blocked focused unfiltered
Predictions offline online overloaded

blocked or offline = too many similarities to past experiences = UNDERWHELM
unfiltered or overloaded = too many differences from past experiences = OVERWHELM
focused or online = manageable amount of differences or similarities from past experiences = FUN

Sensory Input Prediction Past Experiences Phenomenon Mountain
1 too little too little blocked, offline UNDERWHELM foot
2 too little too much blocked, overloaded UNDERWHELM-OVERWHELM slope
3 too little just right blocked, online UNDERWHELM-FUN slope
4 just right too little focused, offline FUN-UNDERWHELM slope
5 just right just right focused, online FUN (a.k.a. learning) peak
6 just right too much focused, overloaded FUN-OVERWHELM slope
7 too much just right unfiltered, online OVERWHELM-FUN slope
8 too much too little unfiltered, offline OVERWHELM-UNDERWHELM slope
9 too much too much unfiltered, overloaded OVERWHELM foot

Area 1 and Area 9 are moments that are not fun.
Area 2 and Area 8 are moments that just pass the time.
Area 3 and Area 4 are fun moments that eventually become underwhelming.
Area 6 and Area 7 are fun moments that eventually become overwhelming.
Area 5 are moments that are fun!

Discussion

I’d like to start by thanking the author for including a note about accessibility concerns. I think this is a great idea, and you’ve inspired me to start doing this, too. Is there not a standard accessibility statement somewhere? Something like the minimum technical requirements for running software?

Okay, so with this said, I’ll start my discussion.


From the opening, I’m really into this story’s chess setting and I find myself suspending disbelief.

So this is cool — now I’m going to be playing chess. I haven’t done this in so long. Since I know the basic rules, and I toggled MOVES ON to speed up my orientation with the ASCII chess board, I feel like my prediction space feels just right. I’m moving fast to the mesa of Area 3, with expectations to keep up this pace to the summit of Area 5.


The game provides a narration for the first move that I make. I’m liking this! Now, I might be biased for saying this, but for me, this narration fast-tracked me to the peak of Area 5.

My terrible chess performance leads to the board being reset more times than I hoped. Even so, the narration of my attempts was fun to read, so I keep trying again. I was sad to see that sometimes a narration was a spartan extra-diegetic description instead of that lively diegetic prose from the introduction.


Eventually, I recourse to a brute-force search to find a winning move set. This tactic shifts my context from reading to problem solving, and now I’m barely holding onto a suspension of disbelief. My predictions are barely happening and my sensory input is low. I’m on the edge of the north mesa, and looking down I see the foot of the mountain. But this is nobody’s fault except my own, and strictly due to my inexperience with endgames.

My brute-force search has some success, and I finally obtain the STALEMATE, MATE achievement. But at this point, my problem-solving mode has replaced my literary suspension of disbelief, so I decide to move on.

Conclusion

The path to the peak of this mountain of fun is direct and fast! And even though the path down proved just as expedient, I still loved my view from atop the summit around Area 5.

I think a serious chess player would definitely have fun playing this narration of this endgame!


Many thanks to Andrew Schultz for making You Won’t Get Her Back and congratulations for being part of ParserComp 2022!!

1 Like

Thanks for this review! Your mentioning brute force brings up one thing I want to discuss in a postmortem. I think it’s valuable to have puzzles that seem like you can brute-force everything, but there’s one more thing to notice. The question is how to make it fair and not too obscure!

In this case, I there was some synchronicity, as I’d just gone through my daily free “survival rush” puzzle gauntlet at chess.com (where you keep doing harder puzzles until you get 3 wrong) and for a few, I was lucky enough to have a new idea once I ran out of brute-forcing.

And it’s interesting to see how my brute-forcing has evolved over time, for chess or parser game puzzles, along with my intuition for when my brute forcing doesn’t work. But it’s outside the scope of this thread!

I’ve mentioned in other reviews that I’m not sure if the twist is fully fair, but it’s interesting to see the balance of “I got it” and “I didn’t” with a relative lack of vitriol in either case. And I wanted the early failures to at least be fun! I have a few ideas for cluing later, which may even slowly hint at the right solution, but I don’t want to make it too obvious too soon.

And thanks for this review thread–selfish “yay I got one more review to help with a quick post-comp release” aside, I think we all can flag a bit in the late middle of the competition, and anything that helps us procrastinate less before the final stretch is good motivation indeed. There are always vote-dumps, but I know I’m that much more uneasy about entries I judge late as often I may not have seen everything I wanted to or should have.

1 Like

I love chatting with designers about their process, so thank you for this reply!


I totally agree! I love this design approach and I’ve tried it several times. But for me, each time took so much effort to get right. I think you did a good job here and I had fun playing your game. :slight_smile:

1 Like

Things That Happened In Houghtonbridge

By Dee Cooke

Summary

I’ve accidentally broken into a house and now I can’t find my way out!

Mountain of Fun

What is a Mountain of Fun?

I use Barrett’s concepts of an allostatic-interoceptive brain to inspire a new model of fun, which I’m calling the mountain of fun. In a nutshell, this model compares and contrasts past and present experiences. But please keep in mind that since variation is the norm with people, there is a degree of subjectivity when using this model to describe one’s experience.

Brain too little just right too much
Sensory Input blocked focused unfiltered
Predictions offline online overloaded

blocked or offline = too many similarities to past experiences = UNDERWHELM
unfiltered or overloaded = too many differences from past experiences = OVERWHELM
focused or online = manageable amount of differences or similarities from past experiences = FUN

Sensory Input Prediction Past Experiences Phenomenon Mountain
1 too little too little blocked, offline UNDERWHELM foot
2 too little too much blocked, overloaded UNDERWHELM-OVERWHELM slope
3 too little just right blocked, online UNDERWHELM-FUN slope
4 just right too little focused, offline FUN-UNDERWHELM slope
5 just right just right focused, online FUN (a.k.a. learning) peak
6 just right too much focused, overloaded FUN-OVERWHELM slope
7 too much just right unfiltered, online OVERWHELM-FUN slope
8 too much too little unfiltered, offline OVERWHELM-UNDERWHELM slope
9 too much too much unfiltered, overloaded OVERWHELM foot

Area 1 and Area 9 are moments that are not fun.
Area 2 and Area 8 are moments that just pass the time.
Area 3 and Area 4 are fun moments that eventually become underwhelming.
Area 6 and Area 7 are fun moments that eventually become overwhelming.
Area 5 are moments that are fun!

Discussion

The initial paragraphs are descriptive and utilitarian, but soon I catch on that all the best prose is in object descriptions, and I suspend my disbelief.

My initial impression of the help section is great. Concise and chunked and helpful!

Visualizing my movement in terms of compass points is frustrating because I never feel that I have enough sensory input to make my predictions feel comfortable.


I love all the great narration that comes with examining the environment! I think I remember this being environmental storytelling, right? Almost all of my predictions are rewarded with new sensory input, which is really fun. Up to now, everything feels just right. It’s a great view from Area 5 at the peak of the mountain.


I’m happy to see that a conversation that I have is implemented with a choice list that isn’t cognitively dissonant.


Soon, I settle into a nice rhythm of looking, predicting, and doing. This creates a pleasing forward momentum through the story. So far, I’m loving this environmental storytelling approach. More often than not, my intuition for a prediction ends up being right, and I think this is due to the great sensory input and narration in the environment.


Eventually, I’m roaming around the inside a house while trying to find a way out. I eventually exhaust all of my predictions to find a way out. I find myself moving down through the mesa of the mountain past Area 4.

The hint that I ask for doesn’t put me back on track. I examined the attic trapdoor already, and I couldn’t find anything else there besides a scribbling. My inexperience with the genre conventions finds me out of sensory input and predictions. Through nobody’s fault but my own, I descend down to the foot of the mountain.

As a last ditch effort to start another accent, I peek at the full verb list. It is cool to see so many verbs! But ultimately, this doesn’t stop my delay.

Conclusion

I got stuck in Beverley’s house after rifling through her desk while looking for a pipe wrench and caring around a phone, brass key, diary, incense packet, and vase.


This approach is really fun! When things are moving forward, I can’t ask for anything more — I get a total suspension of disbelief, I think the sensory input is great, and all of my predictions feel earned and just right.


Many thanks to Dee Cooke for making Things That Happened In Houghtonbridge and congratulations for being part of ParserComp 2022!!

1 Like

Thanks for your review!

For where you got stuck: try taking a closer look at the incense packet.

There’s also a walkthrough to download from the Itch page if needed :slightly_smiling_face:

1 Like

Midnight at Al’s Self Storage, Truck Rentals, and Discount Psychic Readings

By Thomas Insel

Summary

Despite cramped hallways and finicky equipment, I finish all of my work in time to watch the sun rise. Is it too late — or too early — for that nap I was looking forward to taking in the break room?

Mountain of Fun

What is a Mountain of Fun?

I use Barrett’s concepts of an allostatic-interoceptive brain to inspire a new model of fun, which I’m calling the mountain of fun. In a nutshell, this model compares and contrasts past and present experiences. But please keep in mind that since variation is the norm with people, there is a degree of subjectivity when using this model to describe one’s experience.

Brain too little just right too much
Sensory Input blocked focused unfiltered
Predictions offline online overloaded

blocked or offline = too many similarities to past experiences = UNDERWHELM
unfiltered or overloaded = too many differences from past experiences = OVERWHELM
focused or online = manageable amount of differences or similarities from past experiences = FUN

Sensory Input Prediction Past Experiences Phenomenon Mountain
1 too little too little blocked, offline UNDERWHELM foot
2 too little too much blocked, overloaded UNDERWHELM-OVERWHELM slope
3 too little just right blocked, online UNDERWHELM-FUN mesa
4 just right too little focused, offline FUN-UNDERWHELM mesa
5 just right just right focused, online FUN (a.k.a. learning) peak
6 just right too much focused, overloaded FUN-OVERWHELM mesa
7 too much just right unfiltered, online OVERWHELM-FUN mesa
8 too much too little unfiltered, offline OVERWHELM-UNDERWHELM slope
9 too much too much unfiltered, overloaded OVERWHELM foot

Area 1 and Area 9 are moments that are not fun.
Area 2 and Area 8 are moments that just pass the time.
Area 3 and Area 4 are fun moments that eventually become underwhelming.
Area 6 and Area 7 are fun moments that eventually become overwhelming.
Area 5 are moments that are fun!

Discussion

I think the introduction (especially the opening sentence) is very effective at setting a scene. By the time I can start interacting, I have a suspension of disbelief and I’m ready to start my evening shift.

I find that there’s not much sensory input happening from the environment, but my prediction space is low because I have a clear understanding of my next steps. I’m already on the mesa of Area 3.

I love my forward momentum. I’m comfortably on the mesa after I finish my first task. For few moments, some nice environmental storytelling places me around the peak at Area 5. I’m looking forward to more environmental storytelling to keep me here at the peak.

Eventually, some environment and inventory fiddling slows my momentum down a bit. I get stuck in the elevator, which this feels like a bug, not a feature. And while UNDO does rescue me, I find myself at the foot of the mountain, eager to start my ascent back to the mesa and regain a suspension of disbelief. My remaining interactions with the elevator puts me in problem solving mode, where I find myself on the north slope of Area 2.

My forward momentum picks back up, and before I know it, I’m at the end! I never get back a suspension of disbelief, but I do end on the mesa at Area 3. I love that I finished this work, even with my limited knowledge of genre conventions and without reaching for walk-through.

Conclusion

This work did a great job getting me to and keeping me at the mesa at Area 3, with occasional highs and lows around the peak and the foot of the mountain. I am definitely looking forward to more midnight traipsing at Al’s!


Many thanks to Thomas Insel for making Midnight at Al’s Self Storage, Truck Rentals, and Discount Psychic Readings and congratulations for being part of ParserComp 2022!!

Desrosier’s Discovery

By Ben Ehrlich and Isabel Stewart

Summary

Not wanting to go to my grave with any regret, I accept an invitation to meet an old friend at a remote island. I never make it back, which is, well — it’s rather regrettable.

Mountain of Fun

What is a Mountain of Fun?

I use Barrett’s concepts of an allostatic-interoceptive brain to inspire a new model of fun, which I’m calling the mountain of fun. In a nutshell, this model compares and contrasts past and present experiences. But please keep in mind that since variation is the norm with people, there is a degree of subjectivity when using this model to describe one’s experience.

Brain too little just right too much
Sensory Input blocked focused unfiltered
Predictions offline online overloaded

blocked or offline = too many similarities to past experiences = UNDERWHELM
unfiltered or overloaded = too many differences from past experiences = OVERWHELM
focused or online = manageable amount of differences or similarities from past experiences = FUN

Sensory Input Prediction Past Experiences Phenomenon Mountain
1 too little too little blocked, offline UNDERWHELM foot
2 too little too much blocked, overloaded UNDERWHELM-OVERWHELM slope
3 too little just right blocked, online UNDERWHELM-FUN slope
4 just right too little focused, offline FUN-UNDERWHELM slope
5 just right just right focused, online FUN (a.k.a. learning) peak
6 just right too much focused, overloaded FUN-OVERWHELM slope
7 too much just right unfiltered, online OVERWHELM-FUN slope
8 too much too little unfiltered, offline OVERWHELM-UNDERWHELM slope
9 too much too much unfiltered, overloaded OVERWHELM foot

Area 1 and Area 9 are moments that are not fun.
Area 2 and Area 8 are moments that just pass the time.
Area 3 and Area 4 are fun moments that eventually become underwhelming.
Area 6 and Area 7 are fun moments that eventually become overwhelming.
Area 5 are moments that are fun!

Discussion

The opening choice gives me cognitive dissonance because the introduction doesn’t have enough sensory input to scope down my predictions to a disconfirming answer. I hope this isn’t a precedent for this work’s choice mechanics. But for now, I’m on the north slope on Area 2 and without further delay I move forward.


I can’t seem to find a help section and HELP isn’t working. I’m a bit worried now, because I need all the help I can get.


Thankfully, the prose includes enough sensory input to reliably induce a valid prediction from me. For me, this is excellent design, which now puts me on the north mesa around Area 3. I love this and I’m looking forward being on the summit of the mountain of fun.

But some of the prose is starting to read like an inventory list, which starts to make me wander around the north slope.


Sooner than I’d hoped, there is another choice with insufficient sensory input to make a prediction. And then another choice with insufficient sensory input leads me to reach both my final decision and my arrival at the foot of the mountain.

Conclusion

I stopped after receiving a “game over” when I employed “Chekhov’s gun” (i.e., I find a gun and then I find a monster, which is enough sensory input to induce a prediction to “shoot monster with gun”).


The parser made me feel like all of my predictions were valid, which gave me great forward moment and also helped to suspend some disbelief. If continue-or-restart choices were preceded with more effective sensory input to induce a comfortable prediction, I could easily see myself on the peak of the mountain of fun.


Many thanks to Ben Ehrlich and Isabel Stewart for making Desrosier’s Discovery and congratulations for being part of ParserComp 2022!!

Improv: Origins

By Neil deMause

Summary

I was ensured that my Ingenuity degree would thoroughly prepare me for my first superhero gig. Yeah, right — as if! Well, except for the rubber bands. I didn’t believe it at the time, but they were right about the rubber bands. So many rubber bands…

Mountain of Fun

What is a Mountain of Fun?

I use Barrett’s concepts of an allostatic-interoceptive brain to inspire a new model of fun, which I’m calling the mountain of fun. In a nutshell, this model compares and contrasts past and present experiences. But please keep in mind that since variation is the norm with people, there is a degree of subjectivity when using this model to describe one’s experience.

Brain too little just right too much
Sensory Input blocked focused unfiltered
Predictions offline online overloaded

blocked or offline = too many similarities to past experiences = UNDERWHELM
unfiltered or overloaded = too many differences from past experiences = OVERWHELM
focused or online = manageable amount of differences or similarities from past experiences = FUN

Sensory Input Prediction Past Experiences Phenomenon Mountain
1 too little too little blocked, offline UNDERWHELM foot
2 too little too much blocked, overloaded UNDERWHELM-OVERWHELM slope
3 too little just right blocked, online UNDERWHELM-FUN mesa
4 just right too little focused, offline FUN-UNDERWHELM mesa
5 just right just right focused, online FUN (a.k.a. learning) peak
6 just right too much focused, overloaded FUN-OVERWHELM mesa
7 too much just right unfiltered, online OVERWHELM-FUN mesa
8 too much too little unfiltered, offline OVERWHELM-UNDERWHELM slope
9 too much too much unfiltered, overloaded OVERWHELM foot

Area 1 and Area 9 are moments that are not fun.
Area 2 and Area 8 are moments that just pass the time.
Area 3 and Area 4 are fun moments that eventually become underwhelming.
Area 6 and Area 7 are fun moments that eventually become overwhelming.
Area 5 are moments that are fun!

Discussion

The introduction starts me off with a suspension of disbelief, and now I’m eager to a make a great first impression at my first superhero gig.


From the start, there is enough sensory input in the environment to induce some comfortable predictions. I enjoy a nice pace forward to the mesa at Area 3.

Sometimes, the prose reads more like an inventory list, which for me, rattles my literary suspension of disbelief. However, I’m still having fun on the north mesa.


When the jokes land, everything is really fun. For me, the environmental silliness — as opposed to environmental storytelling — puts me in Area 5 at the peak.


Eventually, the prose’s sensory input starts to run low, then my predictions run low. This slows both my momentum and the flow of comedy. A delay starts to build up, but before I reach my limit, I get a sudden burst of progress. My excite fades when I realize my forward momentum has arrived at a decision to restart everything from the beginning.

Conclusion

I got turned into a toad, but before that happened, I found a holographic phone and rummaged through a chest where there was more rubber bands. I don’t think I even got close to opening up that safe.


I was definitely having a lot of fun when the forward momentum was bringing out the best of the environmental silliness.


Many thanks to Neil deMause for making Improv: Origins and congratulations for being part of ParserComp 2022!!

Radio Tower

By Brojman

Summary

Deciding to sleep through a rain storm was not in my best interest. I never wake up again.

Mountain of Fun

What is a Mountain of Fun?

I use Barrett’s concepts of an allostatic-interoceptive brain to inspire a new model of fun, which I’m calling the mountain of fun. In a nutshell, this model compares and contrasts past and present experiences. But please keep in mind that since variation is the norm with people, there is a degree of subjectivity when using this model to describe one’s experience.

Brain too little just right too much
Sensory Input blocked focused unfiltered
Predictions offline online overloaded

blocked or offline = too many similarities to past experiences = UNDERWHELM
unfiltered or overloaded = too many differences from past experiences = OVERWHELM
focused or online = manageable amount of differences or similarities from past experiences = FUN

Sensory Input Prediction Past Experiences Phenomenon Mountain
1 too little too little blocked, offline UNDERWHELM foot
2 too little too much blocked, overloaded UNDERWHELM-OVERWHELM slope
3 too little just right blocked, online UNDERWHELM-FUN mesa
4 just right too little focused, offline FUN-UNDERWHELM mesa
5 just right just right focused, online FUN (a.k.a. learning) peak
6 just right too much focused, overloaded FUN-OVERWHELM mesa
7 too much just right unfiltered, online OVERWHELM-FUN mesa
8 too much too little unfiltered, offline OVERWHELM-UNDERWHELM slope
9 too much too much unfiltered, overloaded OVERWHELM foot

Area 1 and Area 9 are moments that are not fun.
Area 2 and Area 8 are moments that just pass the time.
Area 3 and Area 4 are fun moments that eventually become underwhelming.
Area 6 and Area 7 are fun moments that eventually become overwhelming.
Area 5 are moments that are fun!

Discussion

There is a lot going as soon as I turn this game on, which starts me on the south foot of the mountain. I soon realize the quad-screen user interface, color-coded words, and instruction dump is here to help me. Perhaps a layered reveal would help acclimate a new player? Having said all that, I definitely see all this being helpful to keep sensory input and predictions on track! After dedicating myself to read through everything, I’m on the north slope in Area 2.


Once I’m past the instructions, the beginning prose draws me into a suspension of disbelief! I move to the north mesa in Area 4, ready to check up on my friend during a bad storm. But as soon as the action starts, the prose reads like an insurance appraisal. (Does the player character have aspirations to be an insurance claim adjuster? Is that the real horror here?!)


After getting used to the quad-screen user interface, I notice, in addition to the awesome map, a list of available actions for the current room. I can see myself — having run low on sensory input and predictions — trying to brute force through this list and these color-coded words. But since I’m still learning the genre’s conventions, I’m glad for the help.


(I’d like to digress for a moment about choice lists. I think I understand why this genre advises against the idea of revealing a choice list. A hidden choice list intends to create the illusion of breadth and depth; there is a common convention that this illusion causes an audience’s prediction to be more satisfying. In a way, I suppose that revealing — instead of hiding — a choice list is functionally equivalent to breaking an audience’s suspension of disbelief.)


When I inspect a room’s feature, the appraisal-like sensory input clashes against my suspension of disbelief for the setting. This doesn’t move me off the north mesa, but I do shift over to Area 3. For me, combining environmental storytelling with a comfortable pace forward usually takes me to Area 5.


The parser’s requirement for exactly-typed commands is chipping away at my suspension of disbelief.


I soon settle into a flow of matching items from one choice list to another. Now, this creates some amazing forward momentum! I know exactly what I should be doing next, and I’m usually working on a next step without much delay. But the prose has low sensory input, causing me to have fewer stateless predictions. This puts me in a superposition between Area 1 and Area 3.


Before I can start another ascent back to the mesa, I receive some sensory input for a reasonable prediction, but that prediction leads me to a decision to restart from the beginning. I’ve discussed this design approach in a previous review, but I’ll go over this again here. For me, this happened because I employed “Chekhov’s gun” (i.e., I find a bed and then I see a flashing button labeled sleep, which is enough sensory input to induce a prediction to “sleep”).

Restarting from the beginning will leave me at Area 1 until I reach this juncture again, so I decide to move on.

Conclusion

I got a strong hint to sleep in a bed, where I was promptly stabbed to death.


For me, with a bit more sensory input (perhaps through environmental storytelling), I can see this approach being very fun.


Many thanks to Brojman for making Radio Tower and congratulations for being part of ParserComp 2022!!