Markov Text Adventure Analysis
This is a Markov analysis of the The Teeny Tiny Mansion. Please see Evan Miller's blog for the basic information on what this is supposed to do.
Usage:
julia MarkovTextAdventure.jl
or
python MarkovTextAdventure.py
Typical output:
Scenario 1: Green-key bug and help-me bug
=> There is a dead end :-(
=> Calculating how bad it is...
=> Still calculating...
=> This bug affects 78.46% of button-mashing players
=> Valid states: 1680
=> MAX_FINISH_DEPTH: 14
Scenario 2: Green-key bug only
=> There is a dead end :-(
=> Calculating how bad it is...
=> Still calculating...
=> This bug affects 25.00% of button-mashing players
=> Valid states: 1664
=> MAX_FINISH_DEPTH: 14
Scenario 3: Help-me bug only
=> There is a dead end :-(
=> Calculating how bad it is...
=> Still calculating...
=> This bug affects 71.28% of button-mashing players
=> Valid states: 1680
=> MAX_FINISH_DEPTH: 14
Scenario 4: No bugs (hopefully)
=> 59 recurrent classes and no dead ends! Hooray!
=> Verifying the result...
=> Still calculating...
=> This bug affects -0.00% of button-mashing players
=> Valid states: 1664
=> MAX_FINISH_DEPTH: 14
Python differences
The Python port (contributed by hackerb9 has some differences from the Julia version.
Changes:
- MarkovTextAdventure.py runs on Python (2 and 3).
- Uses Arnoldi Iteration and sparse arrays.
- Runs faster, requires less memory.
- Now works on CPUs from the 1990's which lack SSE2 (woohoo!).
- Does not yet implement % button-masher code.
To do:
- Calculate % of button-mashers affected.
- Make matrix more sparse by culling actions that go "backward" .
- Allow Alice and Bob to be eaten by a GRUE.
NB: This is a work of ergodic fiction, suitable for appropriate age groups only.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent