This is a study in storytelling and morphology, eventually combining Georges Polti's "The Thirty-Six Dramatic Situations" with aspects of Joseph Campbell, David Adams Leeming, and Phil Cousineau's mythology patterns to create story frameworks. The ultimate goal is to study how their pattens could be used interactively to create procedurally-generated, player-driven stories. What you see right now are baby steps, but an important foundation for future work.
Character names are selected from a list provided by The Office for National Statistics, UK (England and Wales, 2009 database).
All stories are randomly generated on refresh.
Complex situation generation (with relationships)
This is where the bulk of my work is going: an attempt to draw more meaningful relationships between characters, based on a crude mix of two (or more) of Polti's dramatic situations. It's often a bit of a mess, but occasionally touches on a bit of brilliance.
I've culled a few of the situations that the algorithm can't quite handle yet. I'm putting them back in as the algorithm becomes more robust.
Abduction / Fatal imprudence. Louis is abducted by Sonny and is the victim of the imprudent Sonny. Sophie is the guardian of Louis. Sonny is the imprudent.
Crime pursued by vengeance / Supplication. Erin is a criminal pursued by Dylan and persecutes Dylan. Emily is a power in authority whose decision is doubtful.
Necessity of sacrificing loved ones / Recovery of a lost one. Emily is a hero who is forced to sacrifice their beloved Chloe and seeks and finds the lost Chloe. There is a necessity for the sacrifice.
Complex situation generation (no relationships)
Similar to my work above, but without attempting to draw any relationships between the characters.
Loss of loved ones / Discovery of the dishonour of a loved one. Samara is a kin spectator and the discoverer. Harvey is a kin slain. Molly is an executioner and the guilty one.
Murderous adultery / Daring enterprise. Lilly-May is another adulterer and an adversary. Matilda is an adulterer and a bold leader. Kieron is the betrayed partner. There is an object of desire.
Conflict with a god / The enigma. Tyler is a mortal and an interrogator. Alicja is an immortal and the seeker.
Simple situation generation
Nothing more than one of Polti's dramatic situations combined with random names. The most basic story-starter.
Vengeance taken for kin upon kin. Olivia is a relative of both. Coby is a Guilty kin. Mylee is an Avenging kin.
Recovery of a lost one. Ayah is a Seeker. Henry is the One Found.
Adultery. Courtney is a Deceived Spouse. Joshua is another Adulterer. Isla is an Adulterer.
The same algorithm as the top experiment, but mixing together four plots instead of two. The reason it doesn't really work is because it attempts to draw relationships wherever possible, resulting in entirely too many connections for too few characters. Many of the situations don't work when applied to the same characters, like a slain character still being able to discover something. Sometimes, however, it hits a nice balance by fluke. It's a curious example of the limitations of the current algorithm.
Vengeance taken for kin upon kin / Fatal imprudence / Abduction / Remorse. Lizzy is a guilty kin and is the victim of the imprudent Callum and is abducted by Callum and is the victim of Callum. Jack is the guardian of Lizzy and is an interrogator. Callum is an avenging kin and is the imprudent. Shreeya is a relative of both.
Vengeance taken for kin upon kin / Madness / Discovery of the dishonour of a loved one / Ambition. Ruby is a guilty kin and is has gone insane and discovers the guilt of their beloved Kian and is an ambitious person. Kian is an avenging kin and is the victim of Ruby and is adversaries with Ruby. Oliver is a relative of both. There is something coveted.
Obtaining / Crime pursued by vengeance / Self-sacrifice for kin / Falling prey to cruelty or misfortune. Maryam solicits their adversary Mya and is a hero who sacrifices themselves for their kin Rayne. Rayne causes misfortune to fall on Maryam. Mya refuses the solicitation of Maryam and is a criminal pursued by Maryam.
Name generation
Pulls random names from UK census data, weighted for popular names. Also cross-references the male and female list to find gender-neutral options. It can currently retrieve around 8k unique names.
Male: Hasan Female: Millie Gender-neutral: Dylan
Male: Benjamin Female: Evie Gender-neutral: Hannan
Male: George Female: Megan Gender-neutral: Casey
This is a study in storytelling and morphology, eventually combining Georges Polti's "The Thirty-Six Dramatic Situations" with aspects of Joseph Campbell, David Adams Leeming, and Phil Cousineau's mythology patterns to create story frameworks. The ultimate goal is to study how their pattens could be used interactively to create procedurally-generated, player-driven stories. What you see right now are baby steps, but an important foundation for future work.
Character names are selected from a list provided by The Office for National Statistics, UK (England and Wales, 2009 database).
All stories are randomly generated on refresh.
Complex situation generation (with relationships)
This is where the bulk of my work is going: an attempt to draw more meaningful relationships between characters, based on a crude mix of two (or more) of Polti's dramatic situations. It's often a bit of a mess, but occasionally touches on a bit of brilliance.
I've culled a few of the situations that the algorithm can't quite handle yet. I'm putting them back in as the algorithm becomes more robust.
Revolt / Conflict with a god. Lucia conspires against the tyrant Isabelle and is a mortal in conflict with the immortal Isabelle. Isabelle is a tyrant.
Revolt / Remorse. Keiran conspires against the tyrant Scott and is the victim of Scott. Arabella is an interrogator. Scott is a tyrant.
Loss of loved ones / Abduction. Molly is slain by William and is abducted by William. Daisy sees the slaying of Molly and is the guardian of Molly.
Complex situation generation (no relationships)
Similar to my work above, but without attempting to draw any relationships between the characters.
Falling prey to cruelty or misfortune / Murderous adultery. Aimee is an unfortunate and another adulterer. Frederick is the master and an adulterer. Luca is the betrayed partner.
Rivalry of kin / Involuntary crimes of love. Jacob is a preferred kin and a lover. Evan is the beloved. Domonic is a rejected kin and the revealer of their crime. There is an object of rivalry.
Deliverance / The enigma. Leighton is a rescuer and an interrogator. Rehan is an unfortunate. Tobias is a threatener and the seeker.
Simple situation generation
Nothing more than one of Polti's dramatic situations combined with random names. The most basic story-starter.
Madness. Chloe is the Victim. Lilly is has gone insane.
Vengeance taken for kin upon kin. Emily is a relative of both. Ella is a Guilty kin. Ghulam is an Avenging kin.
Enmity of kin. Jay is a Hated kin. Layla is a Malevolent kin.
The same algorithm as the top experiment, but mixing together four plots instead of two. The reason it doesn't really work is because it attempts to draw relationships wherever possible, resulting in entirely too many connections for too few characters. Many of the situations don't work when applied to the same characters, like a slain character still being able to discover something. Sometimes, however, it hits a nice balance by fluke. It's a curious example of the limitations of the current algorithm.
Rivalry of superior vs. inferior / Fatal imprudence / Deliverance / Falling prey to cruelty or misfortune. Isabel is the victim of the imprudent Alice. Tyler rescues Isabel and causes misfortune to fall on Isabel. Alice a superior rival to Isabel and is the imprudent and threatens Isabel. There is an object of rivalry.
Daring enterprise / Supplication / Obtaining / Ambition. Lilly-Mae is a bold leader and solicits their adversary Kai and is an ambitious person. Timur is an adversary. Kai persecutes Lilly-Mae and refuses the solicitation of Lilly-Mae and is adversaries with Lilly-Mae. Gemma is a power in authority whose decision is doubtful. There is an object of desire, and something coveted.
Falling prey to cruelty or misfortune / Necessity of sacrificing loved ones / Vengeance taken for kin upon kin / Crimes of love. Kamile is a hero who is forced to sacrifice their beloved Max and is a guilty kin and commits a crime because of their love for Max. Max causes misfortune to fall on Kamile. Michael is an avenging kin. Maria is a relative of both. There is a necessity for the sacrifice.
Name generation
Pulls random names from UK census data, weighted for popular names. Also cross-references the male and female list to find gender-neutral options. It can currently retrieve around 8k unique names.
Male: Jacob Female: Macey Gender-neutral: Bailey
Male: Robert Female: Charlotte Gender-neutral: Miley
Male: Ben Female: Eleanor Gender-neutral: Brooke
This is a study in storytelling and morphology, eventually combining Georges Polti's "The Thirty-Six Dramatic Situations" with aspects of Joseph Campbell, David Adams Leeming, and Phil Cousineau's mythology patterns to create story frameworks. The ultimate goal is to study how their pattens could be used interactively to create procedurally-generated, player-driven stories. What you see right now are baby steps, but an important foundation for future work.
Character names are selected from a list provided by The Office for National Statistics, UK (England and Wales, 2009 database).
All stories are randomly generated on refresh.
Complex situation generation (with relationships)
This is where the bulk of my work is going: an attempt to draw more meaningful relationships between characters, based on a crude mix of two (or more) of Polti's dramatic situations. It's often a bit of a mess, but occasionally touches on a bit of brilliance.
I've culled a few of the situations that the algorithm can't quite handle yet. I'm putting them back in as the algorithm becomes more robust.
Necessity of sacrificing loved ones / Abduction. Matilda is a hero who is forced to sacrifice their beloved Olivia and is abducted by Benjamin. Olivia is the guardian of Matilda. There is a necessity for the sacrifice.
Discovery of the dishonour of a loved one / Involuntary crimes of love. Ellie discovers the guilt of their beloved Ciara and commits a crime because of their love for Jayden. Ciara is the revealer of their crime.
Self-sacrifice for kin / Madness. Sohail is a hero who sacrifices themselves for their kin Benjamin and is has gone insane. Ronnie is the victim of Sohail.
Complex situation generation (no relationships)
Similar to my work above, but without attempting to draw any relationships between the characters.
Madness / The enigma. Isobel is has gone insane and an interrogator. Lydia is the victim and the seeker.
Supplication / Necessity of sacrificing loved ones. Alice is a supplicant and a beloved victim. Carolina is a hero. Mus'Ab is a presecutor. Zak is a power in authority whose decision is doubtful. There is a necessity for the sacrifice.
Deliverance / Recovery of a lost one. Mya is a rescuer and a seeker. Lewis is an unfortunate and the one found. Taylor is a threatener.
Simple situation generation
Nothing more than one of Polti's dramatic situations combined with random names. The most basic story-starter.
Obtaining. Sophie is an Adversary who is refusing. Hamzah is a Solicitor.
Adultery. Maddison is a Deceived Spouse. Marcus is another Adulterer. Lucas is an Adulterer.
Disaster. Lillie-Mae is the Vanquished Power. Jon-Paul is the Victorious Enemy.
The same algorithm as the top experiment, but mixing together four plots instead of two. The reason it doesn't really work is because it attempts to draw relationships wherever possible, resulting in entirely too many connections for too few characters. Many of the situations don't work when applied to the same characters, like a slain character still being able to discover something. Sometimes, however, it hits a nice balance by fluke. It's a curious example of the limitations of the current algorithm.
Remorse / Pursuit / Murderous adultery / Obstacles to love. Sebastian is the victim of Amber and is adulterous with Roxanna and is lovers with Roxanna. Roxanna is an interrogator. Amber is a fugitive being chased by Sebastian and is the betrayed partner. There is an obstacle.
Revolt / Vengeance taken for kin upon kin / Abduction / Rivalry of superior vs. inferior. Ciara conspires against the tyrant Sam and is a guilty kin and is abducted by Sam. Sofia is the guardian of Ciara. Sam is a tyrant and is an avenging kin and a superior rival to Ciara. Rhys is a relative of both. There is an object of rivalry.
Loss of loved ones / Crime pursued by vengeance / An enemy loved / Obstacles to love. Brydie is slain by Eliza and is lovers with their enemy Ethan and is lovers with Ethan. Ethan sees the slaying of Brydie. Eliza is a criminal pursued by Brydie and hates Brydie. There is an obstacle.
Name generation
Pulls random names from UK census data, weighted for popular names. Also cross-references the male and female list to find gender-neutral options. It can currently retrieve around 8k unique names.
Male: Lewis Female: Olivia Gender-neutral: Tyler
Male: Joshua Female: Eva Gender-neutral: Ronnie
Male: Thomas Female: Heidi Gender-neutral: Erin
This is a study in storytelling and morphology, eventually combining Georges Polti's "The Thirty-Six Dramatic Situations" with aspects of Joseph Campbell, David Adams Leeming, and Phil Cousineau's mythology patterns to create story frameworks. The ultimate goal is to study how their pattens could be used interactively to create procedurally-generated, player-driven stories. What you see right now are baby steps, but an important foundation for future work.
Character names are selected from a list provided by The Office for National Statistics, UK (England and Wales, 2009 database).
All stories are randomly generated on refresh.
Complex situation generation (with relationships)
This is where the bulk of my work is going: an attempt to draw more meaningful relationships between characters, based on a crude mix of two (or more) of Polti's dramatic situations. It's often a bit of a mess, but occasionally touches on a bit of brilliance.
I've culled a few of the situations that the algorithm can't quite handle yet. I'm putting them back in as the algorithm becomes more robust.
Remorse / Vengeance taken for kin upon kin. Halle is the victim of Rebecca and is a guilty kin. Fatimah is an interrogator. Rebecca is an avenging kin. Paige is a relative of both.
Ambition / Falling prey to cruelty or misfortune. Arifa is an ambitious person. William causes misfortune to fall on Arifa. Mihaela is adversaries with Arifa. There is something coveted.
Vengeance taken for kin upon kin / Obtaining. Amelia is a guilty kin and solicits their adversary Alisha. Alisha is an avenging kin and refuses the solicitation of Amelia. Jayden is a relative of both.
Complex situation generation (no relationships)
Similar to my work above, but without attempting to draw any relationships between the characters.
Vengeance taken for kin upon kin / Necessity of sacrificing loved ones. Eva is a guilty kin and a beloved victim. Lucas is a hero. Harrison is an avenging kin. Cody is a relative of both. There is a necessity for the sacrifice.
Self-sacrifice for an ideal / Involuntary crimes of love. Gabriela is a hero and a lover. Paige is the beloved. Hannah is the revealer of their crime. There is an ideal. There is something sacrificed.
Adultery / Pursuit. Jordan is another adulterer and the punisher. Reegan is an adulterer. Millie is a deceived spouse and the fugitive.
Simple situation generation
Nothing more than one of Polti's dramatic situations combined with random names. The most basic story-starter.
All sacrificed for passion. Lucian is a Lover. There is an Object of fatal Passion. There is something sacrificed.
Recovery of a lost one. Holly is a Seeker. Amy is the One Found.
Disaster. Dylan is the Vanquished Power. Theo is the Victorious Enemy.
The same algorithm as the top experiment, but mixing together four plots instead of two. The reason it doesn't really work is because it attempts to draw relationships wherever possible, resulting in entirely too many connections for too few characters. Many of the situations don't work when applied to the same characters, like a slain character still being able to discover something. Sometimes, however, it hits a nice balance by fluke. It's a curious example of the limitations of the current algorithm.
Disaster / Rivalry of kin / Revolt / An enemy loved. Matthew was in power but was vanquished by their enemy Jake and is preferred over their kin Jake and conspires against the tyrant Jake and is lovers with their enemy Farid. Jake is a rejected kin and is a tyrant and hates Matthew. There is an object of rivalry.
Daring enterprise / Murderous adultery / Self-sacrifice for an ideal / Abduction. Leon is a bold leader and is adulterous with Daisy and is a hero who is forced to sacrifice themselves for an ideal and is abducted by Naomi. Daisy is an adversary and is the guardian of Leon. Naomi is the betrayed partner. There is an object of desire, an ideal, and something sacrificed.
Daring enterprise / Obtaining / Fatal imprudence / Abduction. Billie is a bold leader and solicits their adversary Adam and is the victim of the imprudent Adam and is abducted by Adam. Glen is an adversary and is the guardian of Billie. Adam refuses the solicitation of Billie and is the imprudent. There is an object of desire.
Name generation
Pulls random names from UK census data, weighted for popular names. Also cross-references the male and female list to find gender-neutral options. It can currently retrieve around 8k unique names.
Male: Joshua Female: Alexa Gender-neutral: Harlie
Male: Hussain Female: Olivia Gender-neutral: Alex
Male: Samuel Female: Jessica Gender-neutral: Mackenzie
This is a study in storytelling and morphology, eventually combining Georges Polti's "The Thirty-Six Dramatic Situations" with aspects of Joseph Campbell, David Adams Leeming, and Phil Cousineau's mythology patterns to create story frameworks. The ultimate goal is to study how their pattens could be used interactively to create procedurally-generated, player-driven stories. What you see right now are baby steps, but an important foundation for future work.
Character names are selected from a list provided by The Office for National Statistics, UK (England and Wales, 2009 database).
All stories are randomly generated on refresh.
Complex situation generation (with relationships)
This is where the bulk of my work is going: an attempt to draw more meaningful relationships between characters, based on a crude mix of two (or more) of Polti's dramatic situations. It's often a bit of a mess, but occasionally touches on a bit of brilliance.
I've culled a few of the situations that the algorithm can't quite handle yet. I'm putting them back in as the algorithm becomes more robust.
Necessity of sacrificing loved ones / Conflict with a god. Archie is a hero who is forced to sacrifice their beloved Ethan and is a mortal in conflict with the immortal Sam. There is a necessity for the sacrifice.
Fatal imprudence / Obstacles to love. Mollie is the victim of the imprudent James and is lovers with Tyler. James is the imprudent. There is an obstacle.
Enmity of kin / Ambition. Tristan hates their kin David and is an ambitious person. David is adversaries with Tristan. There is something coveted.
Complex situation generation (no relationships)
Similar to my work above, but without attempting to draw any relationships between the characters.
Abduction / Deliverance. Travis is an abducted and a rescuer. Macy is their guardian and an unfortunate. Holly is an abductor and a threatener.
Ambition / Abduction. Josh is an ambitious person and the abducted. Aryana is the guardian. Jayden is an adversary and an abductor. There is something coveted.
Murderous adultery / Conflict with a god. Uzair is another adulterer and a mortal. Morgan is an adulterer. Milly is the betrayed partner and an immortal.
Simple situation generation
Nothing more than one of Polti's dramatic situations combined with random names. The most basic story-starter.
Erroneous judgement. Ajwa is a Victim of the Mistake. Wilbur is the Guilty One. Lucy is the Author of the Mistake. Farrah is a Mistaken One.
Supplication. Charlie is a Supplicant. Lucy is a Presecutor. Aidan is a Power in authority whose decision is doubtful.
Erroneous judgement. Katie is a Victim of the Mistake. Kian is the Guilty One. Bella is the Author of the Mistake. Danyal is a Mistaken One.
The same algorithm as the top experiment, but mixing together four plots instead of two. The reason it doesn't really work is because it attempts to draw relationships wherever possible, resulting in entirely too many connections for too few characters. Many of the situations don't work when applied to the same characters, like a slain character still being able to discover something. Sometimes, however, it hits a nice balance by fluke. It's a curious example of the limitations of the current algorithm.
Fatal imprudence / Vengeance taken for kin upon kin / Recovery of a lost one / Involuntary crimes of love. Elliemay is the victim of the imprudent Amandeep and is a guilty kin and seeks and finds the lost Caitlin and commits a crime because of their love for Caitlin. Amandeep is the imprudent and is an avenging kin and is the revealer of their crime. Hannah is a relative of both.
Self-sacrifice for kin / Obtaining / Loss of loved ones / Self-sacrifice for an ideal. Tia-Leigh is a hero who sacrifices themselves for their kin Yvie and solicits their adversary Henry and is slain by Henry and is a hero who is forced to sacrifice themselves for an ideal. Yvie sees the slaying of Tia-Leigh. Henry refuses the solicitation of Tia-Leigh. There is an ideal, and something sacrificed.
Daring enterprise / Self-sacrifice for kin / Loss of loved ones / Revolt. Holly is a bold leader and is a hero who sacrifices themselves for their kin Eman and is slain by Isla and conspires against the tyrant Isla. Eman is an adversary and sees the slaying of Holly. Isla is a tyrant. There is an object of desire.
Name generation
Pulls random names from UK census data, weighted for popular names. Also cross-references the male and female list to find gender-neutral options. It can currently retrieve around 8k unique names.