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Brief Update & Pts for Discussion/Debate: RAIR Lab’s NIMD/Sage R&D

Brief Update & Pts for Discussion/Debate: RAIR Lab’s NIMD/Sage R&D. Selmer Bringsjord (with Andrew Shilliday, Josh Taylor, Jason Wodicka, Marc Destefano) Rensselaer AI & Reasoning (RAIR) Laboratory (SB Director) Department of Cognitive Science Department of Computer Science (SB)

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Brief Update & Pts for Discussion/Debate: RAIR Lab’s NIMD/Sage R&D

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  1. Brief Update & Pts for Discussion/Debate:RAIR Lab’s NIMD/Sage R&D Selmer Bringsjord (with Andrew Shilliday, Josh Taylor, Jason Wodicka, Marc Destefano) Rensselaer AI & Reasoning (RAIR) Laboratory (SB Director) Department of Cognitive Science Department of Computer Science (SB) Rensselaer Polytechnic Institute (RPI) Troy NY 12180 USA 9.4.03

  2. The Rensselaer AI & Reasoning Lab(The RAIR Lab) Intelligent Tutoring Systems (mathematical logic) Over $1million internal seeding Intelligence Analysis Item generation (theorem proving-based generation) synthetic characters/psychological time

  3. Points • RAIR Lab’s web site gives immediate access to almost all our content. • The Sage team should probably collaborate with Cycorp (now that Adam P has left Teknowledge) • We can score performance in Sage in rigorous fashion. • RAIR Lab will be running subjects using micro-scenarios. • Bringsjord will be testing specific hypotheses • The Glass Box should be used for setting up controlled experiments a la psychology of reasoning. • Slate is revolutionary; it will be partially built for ARDA; v1.1 is finished.

  4. RAIR Lab’s NIMD/Sage Web Site

  5. RAIR Lab’s NIMD/Sage Web Site...

  6. vMEM Initially, a Q/A theorem proving-based system in which Questions will be answered by deducing Answers from the knowledge base corresponding to vMEM. This knowledge base will be constructed in keeping with the construction of “deep” characters in narrative. (assert '(alive marc) :name 'marc-alive) (assert '(birthtime marc (date-point 1977 2 10 9 24)) :name 'marc-birthtime) (assert '(biological-mother regina marc) :name 'marc-mother) (assert '(biological-father josephjr marc) :name 'marc-father) (assert '(sister christine marc) :name 'marc-sister) (declare-predicate-symbol 'parent 2 :falsify-code 'irreflexivity-falsifier) (assert '(forall (?person) (not (parent ?person ?person))) :name 'parent-irreflexive) (assert '(forall (?person) (iff (parent ?person) (exists (?person1) (parent ?person ?person1)))) :name 'parent-unary-defintion) (assert '(forall (?person1 ?person2) (iff (parent ?person1 ?person2) (child ?person2 ?person1))) :name 'parent-child-inverse) (assert '(forall (?person1 ?person2) (iff (parent ?person1 ?person2) (or (biological-parent ?person1 ?person2) (adoptive-parent ?person1 ?person2) (step-parent ?person1 ?person2) (foster-parent ?person1 ?person2)))) :name 'parent-subdivision) (assert '(forall (?person) (iff (mother ?person) (exists (?person1) (mother ?person ?person1)))) :name 'mother-unary-defintion) (assert '(forall (?person1 ?person2) (iff (mother ?person1 ?person2) (and (parent ?person1 ?person2) (female ?person1)))) :name 'mother-binary-defintion)) (assert '(forall (?person) (exists (?time-interval) (lifespan ?person ?time-interval))) :name 'all-persons-have-lifespan) (assert '(forall (?person ?time-point ?time-interval) (iff (alive-at-time ?person ?time-point) (and (lifespan ?person ?time-interval) (temporally-intersects ?time-interval ?time-point)))) :name 'define-alive-at-time-point) (assert '(forall (?person) (iff (alive ?person) (alive-at-time ?person now))) :name 'define-alive) Bringsjord & Wodicka speak Cycorp’slanguage...

  7. Selmer’s Hypotheses • Use of Slate will increase as the difficulty of the scenario/case study increases. • Non-analysts with three or more courses in formal logic will outperform trained analysts with years of experience when both groups’ performance is measured in connection with well-defined scenarios. • (It would be most interesting to have three groups to compare: non-analysts trained in formal logic, experienced analysts, and experienced analysts explicitly training in the Wigmorean approach.) • The standard training of analysts is more efficacious when extensive training in formal logic (three or more courses) is added. Best is to train analysts using Sage and Slate!

  8. Running Subjects... RUN MP4s...

  9. Re. Glass Box • Collecting low-level behavior of John Updike won’t tell you how he pulls it off. • VPA on Updike would probably generate fiction-on-the-fly. • Why not move Sage-like/Slate-like approach into the Glass Box itself? • Configure a stimulus as tight, micro-case study; make predictions; run subjects; collect and analyze data.

  10. J-L 1 Suppose that the following premise is true: If there is a king in the hand, then there is an ace in the hand, or else if there isn’t a king in the hand, then there is an ace. What can you infer from this premise? There is an ace in the hand. NO! NO! In fact, what you can infer is that there isn’t an ace in the hand!

  11. Slate...

  12. Slate Architecture-Sketch Deduction Abduction Induction

  13. MARMML:Multi-Agent Reasoning and Mental MetaLogic • Challenge:build a machine reasoner with collaborating agents whose reasoning matches the power of collaborating human reasoners operating in the real world • MARMML: Formal, mechanized reasoner. Acts in and across four dimensions traversed by the best human reasoners: • Modes of reasoning: traditional syntactic proofs, exclusively semantic/visual proofs, and proofs that synthesize the two • Types of reasoning: deductive, inductive, “creative,” abductive • Expressivity of reasoning (syntactic and semantic): propositional, first-order, second-order, …, higher-order, modal, temporal, etc.; and ever more expressive modeling • Reasoning across heterogeneous logical levels: Agent 2 can evaluate and refute Agent 1’s object-level proof with meta-proof P’; Agent 3 can evaluate and refute P’ with meta-meta-proof P’’, etc.

  14. Automated reasoner using multi-agent framework that enables collaborative reasoning (more effective than indiv reasoning) • Natural deduction-style prover reflects human reasoning about human reasoning about… • Spans formal levels of logic (reasoner/meta-reasoner/meta-meta reasoner, etc.) – like human collaborative reasoning • Uses existential graphs (EG), Fitch-style inference, and proofs that involve both semantic models and syntactic reasoning • EG to mechanize human “mental model” reasoning • Fitch-style proofs to mechanize “mental logic” reasoning • Meta-proofs to mechanize the marriage of the these two types of reasoning MARMML Reasoner – some details

  15. Slate v1.1 Complete(Bringsjord, Shilliday, Taylor, Wodicka) Now for the demo...

  16. RAIR Web and R&D Advanced Synthetic Characters MARMML PERI Savant PAI Slate CDs Super Teaching

  17. THE END

  18. SLATE

  19. Slate Hypothesis Generation in our Narrative ScenarioWhat is the destination of the convoy? Mary hits a dead end: How would this work?? SAGE offers:

  20. Slate Hypothesis Generation in our Narrative ScenarioWhat is the destination of the convoy? Mary is “searching” for a proof like… ---------------- PROOF ---------------- 1 [] -Yar(x)|Terrorists(x). 2 [] -Camp(x,aconvoy)| -Accessible(x,aconvoylocation). 3 [] -Village(x,aconvoy)| -Accessible(x,aconvoylocation). 6 [] -CaveSystem(x,y)| -Convoy(y)| -Terrorists(y)| -PresentLocation(y,z)| -Accessible(x,z)|Village($f1(x,y,z),y)|Camp($f2(x,y,z),y)|Destination(x,y). 7 [] -CaveSystem(x,y)| -Convoy(y)| -Terrorists(y)| -PresentLocation(y,z)| -Accessible(x,z)|Village($f1(x,y,z),y)|Accessible($f2(x,y,z),z)|Destination(x,y). 8 [] -CaveSystem(x,y)| -Convoy(y)| -Terrorists(y)| -PresentLocation(y,z)| -Accessible(x,z)|Accessible($f1(x,y,z),z)|Camp($f2(x,y,z),y)|Destination(x,y). 9 [] -CaveSystem(x,y)| -Convoy(y)| -Terrorists(y)| -PresentLocation(y,z)| -Accessible(x,z)|Accessible($f1(x,y,z),z)|Accessible($f2(x,y,z),z)|Destination(x,y). 10 [] -Destination(x,aconvoy). 11 [] Convoy(aconvoy). 12 [] Yar(aconvoy). 13 [] PresentLocation(aconvoy,aconvoylocation). 14 [] CaveSystem(acavesystem19,aconvoy). 15 [] Accessible(acavesystem19,aconvoylocation). 17 [hyper,12,1] Terrorists(aconvoy). 18 [hyper,15,9,14,11,17,13,unit_del,10] Accessible($f1(acavesystem19,aconvoy,aconvoylocation),aconvoylocation)|Accessible($f2(acavesystem19,aconvoy,aconvoylocation),aconvoylocation). 19 [hyper,15,8,14,11,17,13,unit_del,10] Accessible($f1(acavesystem19,aconvoy,aconvoylocation),aconvoylocation)|Camp($f2(acavesystem19,aconvoy,aconvoylocation),aconvoy). 20 [hyper,15,7,14,11,17,13,unit_del,10] Village($f1(acavesystem19,aconvoy,aconvoylocation),aconvoy)|Accessible($f2(acavesystem19,aconvoy,aconvoylocation),aconvoylocation). 21 [hyper,15,6,14,11,17,13,unit_del,10] Village($f1(acavesystem19,aconvoy,aconvoylocation),aconvoy)|Camp($f2(acavesystem19,aconvoy,aconvoylocation),aconvoy). 23 [hyper,19,2,18,factor_simp] Accessible($f1(acavesystem19,aconvoy,aconvoylocation),aconvoylocation). 24 [hyper,20,3,23] Accessible($f2(acavesystem19,aconvoy,aconvoylocation),aconvoylocation). 25 [hyper,21,3,23] Camp($f2(acavesystem19,aconvoy,aconvoylocation),aconvoy). 27 [hyper,25,2,24] $F. ------------ end of proof ------------- on the strength, say, of a key proposition like… % If there is a cave system that's accessible from the convoy's present % location, and it's a convoy of terrorists, and there's no terrorist % camp accessible from the convoy's present location, and there's no % village accessible from its present location, then that cave system is its % destination: all x all y all z ((CaveSystem(x,y) & Convoy(y) & Terrorists(y) & PresentLocation(y,z) & Accessible(x,z) & -(exists z1 (Village(z1,y) & Accessible(z1,z))) & -(exists z2 (Camp(z2,y) & Accessible(z2,z)))) -> Destination(x,y)).

  21. Slate Hypothesis Generation in our Narrative ScenarioWhat is the destination of the convoy? But there are no cave systems nearby either!! Hence Slate models Mary’s fruitless search: =========== start of search =========== given clause #1: (wt=2) 11 [] Convoy(aconvoy). . given clause #2: (wt=2) 12 [] Yar(aconvoy). . given clause #3: (wt=2) 15 [] Bioagents(aconvoy). . given clause #4: (wt=2) 16 [] USBase(amilbase33). . given clause #5: (wt=2) 17 [hyper,12,1] Terrorists(aconvoy). . given clause #6: (wt=3) 13 [] PresentLocation(aconvoy,aconvoylocation). . given clause #7: (wt=3) 14 [] CaveSystem(acavesystem19,aconvoy). . Search stopped because sos empty. ============ end of search ============

  22. Slate Hypothesis Generation in our Narrative ScenarioWhat is the destination of the convoy? Slate introduces the concept of an “attack position,” which must be accessible from the convoy’s present location, and an associated target, which must be wind-accessible from the attack position to bio-agents, and automatically produces a proof that supports Mary being told in simple English that a particular US base is threatened. Here is the proof in a simple simulation, obtained in 1.73 seconds of CPU time. The proof shows that “mountain46” is the convoy’s destination, and “usmilbase33” is the target…

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