Generative Story Worlds as Linear Logic Programs

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Generative Story Worlds as Linear Logic Programs Chris Martens, João Ferreira, Anne-Gwenn Bosser, and Marc Cavazza 1 Presented at Interactive Narrative Technologies June 18, 2014

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Generative Story Worlds as Linear Logic Programs Chris Martens, João Ferreira, Anne-Gwenn Bosser, and Marc Cavazza 2 Presented at Interactive Narrative Technologies June 18, 2014

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3 new programming languages for digital narratives Praxis & Prompter:

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4 OLD programming languages for digital narratives(?) LOGIC

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5 old programming languages for digital narratives LINEAR LOGIC

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6 used linear logic as a programming language (Celf) for specifying narrative worlds; used proof search to generate structured stories. What we did:

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THREE ACTS 7 I. Setup: agent simulation, linear logic, and logic programming II. Payoff: Stories as Proofs III. Promise and Limitations

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9 greet insult compliment gossip ﬂirt ... social verbs: social state: knowledge sentiment emotional state personality belief

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10 verbs: rules causal relationships: resource dependencies

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RULES 11 Narrative Actions ~ Logical implication

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12 the problem with standard logical implication: buy_soda : has(Alice, $1) ^ wants(Alice, soda) 㱺 has(Alice, soda)

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LINEAR LOGIC 13 A -o B

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14 buy_soda : has(Alice, $1) * wants(Alice, soda) -o has(Alice, soda)

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15 A * B A -o B !A

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16 A * B A -o {B} !A

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Logic Programming 17 proof search as program execution

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18 initial state Σ Δ0 Celf query (optional) A Δ0, …, Δ Δ ⊢ A? narrative actions

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Logic Programming 19 A -o {B} Δ, A → Δ, B Δ = arbitrary context of resources A1, …, An

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20 Example in our paper: Shakespearean tragedy world

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21 Shakespearean tragedy world state components: character location, possession, sentiment toward other characters, goals

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22 Shakespearean tragedy world at has anger philia depressed

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23 Shakespearean tragedy world !dead !killed

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24 do/insult : at C L * at C’ L * anger C C’ -o {at C L * at C’ L * anger C C’ anger C’ C * depressed C’}.

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25 do/compliment : at C L * at C’ L * philia C C’ -o {at C L * at C’ L * philia C C’ * philia C’ C}.

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26 do/murder : anger C C’ * anger C C’ * anger C C’ * anger C C’ * at C L * at C’ L * has C weapon -o {at C L * !dead C’ * !murdered C C’ * has C weapon}.

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27 do/mourn : at C L * philia C C’ * dead C’ -o {philia C C’ * at C L * depressed C * depressed C}.

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28 do/becomeSuicidal : at C L * depressed C * depressed C * depressed C * depressed C -o {at C L * suicidal C * wants C weapon}.

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29 do/loot : at C L * dead C' * has C' O * wants C O -o {at C L * has C O}.

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30 do/comfort : at C L * at C' L * suicidal C' * philia C C' * philia C' C -o {at C L * at C' L * philia C C' * philia C' C * philia C' C}.

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31 initial state

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32 story_start : init -o { at romeo town * at montague mon_house * at capulet cap_house * at mercutio town * at nurse cap_house * at juliet town * at tybalt town * at apothecary town * has tybalt weapon * has romeo weapon * has apothecary weapon * ...

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33 ... * anger montague capulet * anger capulet montague * anger tybalt romeo * anger capulet romeo * anger montague tybalt * philia mercutio romeo * philia romeo mercutio * philia montague romeo * philia capulet juliet * philia juliet nurse * philia nurse juliet * neutral nurse romeo * neutral mercutio juliet * neutral juliet mercutio * neutral apothecary nurse * neutral nurse apothecary}.

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34 ﬁnal state

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35 ending_happy : nonfinal * actor C * actor C’ * at C L * at C’ L * married C C’ -o {final}. ending_vengeance : nonfinal * actor C1 * actor C2 * actor C3 * killed C1 C2 * philia C3 C2 * killed C3 C1 -o {final}.

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36 proofs as stories

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37 query: init -o {ﬁnal}

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Nondeterminism 38 A -o {B} Δ, B A -o {C} Δ, C Δ, A

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Nondeterminism 39 A -o {B} C -o {D}

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Nondeterminism 40 A -o {B} Δ, B, C C -o {D} Δ, A, D Δ, A, C

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Nondeterminism 41 A -o {B} Δ, B, C C -o {D} Δ, A, D Δ, A, C Δ, B, D

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42 proof of init -o {ﬁnal}: function (x:init) = let [xs] = r [ys] in …

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43 ... let {[X73, [X74, [X75, [X76, X77]]]]} = do/insult/private [a-tybalt, [a-romeo, [X68, [X66, X72]]]] in let {[X85, [X86, X87]]} = do/becomeSuicidal [a-romeo, [X79, [X41, [X59, [X52, X77]]]]] in let {[X88, [X89, [X90, [X91, X92]]]]} = do/comfort [a-mercutio, [a-romeo, [X78, [X85, [X86, [X81, X83]]]]]] in let {[X101, [!X102, [!X103, X104]]]} = do/murder [a-romeo, [a-tybalt, [X58, [X40, [X76, [X51, [X94, [X96, X27]]]]]]]] in let {[X105, [X106, [X107, X108]]]} = do/compliment/private [a-nurse, [a-juliet, [X46, [X47, X30]]]] in let {[X109, [X110, [X111, X112]]]} = do/compliment/private [a-juliet, [a-nurse, [X106, [X105, X108]]]] in let {[X113, X114]} = do/loot [a-romeo, [a-tybalt, [X101, [X102, [X26, X87]]]]] in ...

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Concurrent Equality 44 r1: A -o B r2: C -o D “apply r1; apply r2” ~= “apply r2; apply r1” if A and C are disjoint

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45 graphical representation of traces

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46 init do/insult/private do/formOpinion/dislike do/compliment/witnessed do/travelTo do/compliment/private do/murder do/marry ending_1 do/steal do/thinkVengefully do/mourn do/becomeSuicidal cleanup/1 do/eroticize do/suicide do/ﬂirt/discrete

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47 do/insult/private do/formOpinion/dislike do/compliment/witnessed do/travelTo private do/murder do/marry do/steal do/thinkVengefully do/mourn do/becomeSuicidal do/suicide ete

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48 queries on sets of traces

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49 > exists ending_1 > exists do/thinkVengefully && ̃link do/thinkVengefully do/murder

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generative exploration informative structure character perspective-agnosticism 50 what does this accomplish?

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51 how do simulation designs fail their authors?

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52 orphan verbs vs causally connected chains

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ACT III Potential & Limitations 53

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54 combining reactive/exploratory + goal-driven behavior: A -o G vs A -o {B} (backward & forward chaining) Additional potential of LL

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55 higher-order rules: (A -o B) -o C Additional potential of LL

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56 higher-order rules: (A -o B) -o C “serendipity:” Forall L. at romeo L * at juliet L -o {eros romeo juliet * at romeo L * at juliet L}) Additional potential of LL

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57 Additional potential of LL dynamic object generation: Exists x:A. ... makeRoom : has(C, magic door) * at C R -o {Exists r:room. !adjacent R r}

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58 limitations

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59 limitations (of the tool) (of the underlying formalism)

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60 limitations of the tool: interactivity history tracking debugging facilities drama management

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61 limitations of the formalism: ability to broadcast actions nondeterminism and control over probabilities

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62 what I plan to address: interactivity debugging facilities ability to “broadcast” actions

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63 PHASES

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Phases (Example) 64 deduplication phase act { … } quiesced act -o {phase dedup}. phase dedup { wants C O * wants C O -o {wants C O}. } quiesced dedup -o {phase act}.

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Phases phase p1 = {...} phase p2 = {...} quiesced p1 -o {some_token * phase p2}. quiesced p2 -o {phase p1}. Blocks connected by speciﬁcation of quiescence behavior 65

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Phases (Example) interactivity phase world = { rule1 : do Action * … -o {…}. rule2 : do Action * … -o {…}. } phase player = { get_input : player_turn -o {read #STDIN}. } 66

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67 also possible to implement: broadcast

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68 also ongoing: phase invariants for each phase, constraints on the context… - as an invariant of the phase - at quiescence programmer-speciﬁed, machine-checked!

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FINALE 69

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70 the point of formalism is to be able to run readable speciﬁcations

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71 the point of formalism is to be able to reason about readable speciﬁcations

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74 linear logic can be used as a programming language for specifying narrative worlds; to generate narratives & analyze their structure; potentially the basis for a richer PL. Takeaway

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FINALE 75 Celf: https://github.com/clf/celf Example from the paper: http://tinyurl.com/int2014-clf Me: Chris Martens @chrisamaphone [email protected] Planning to graduate Summer 2015

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MINUS WORLD (bonus slides) 76

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Cut 77 Δ1 ⊢ A Δ 2, A ⊢ C Δ 1, Δ 2 ⊢ C

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Frame Property 78 If Δ1 ⊢ A then Δ1, Δ2 ⊢ A * ⨂Δ2

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Frame Property (alt) 79 If Δ1 → Δ2 then Δ1, Δ’ → Δ2, Δ’

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Relationship between step and deductions 80 Δ1 → Δ2 iff for all C Δ2 ⊢ C implies Δ1 ⊢ C

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81 LOGICS are formalisms with composable consequences

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82 LOGICS are formalisms with composable consequences Δ ⊢ A Δ’, A ⊢ C Δ’, Δ ⊢ C

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Phases (Example) Broadcast phase act { do C A * in_room C R -o {broadcast C A R}. } quiesced act -o {phase broadcast}. phase broadcast { broadcast C A R * in_room C' R -o {notice C' C A * broadcast C A R}. } quiesced broadcast -o {phase notice}. 83

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Phases (Example) Broadcast 84 phase notice { broadcast C A R * notice C' C A -o {react C' C A * in_room C' R * broadcast C A R}. } quiesced notice * broadcast _ _ _ -o {phase react}. phase react { react C C' (murder ...) * philia C C' -o {...} } quiesced react -o {phase act}.

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Phases delimited subsignatures connected by speciﬁcations of quiescence behavior. 85 quiesced P * State -o {phase P’ * State’}. arbitrarily many phases looping + branching