S.C. Shapiro Knowledge Representation and Reasoning Stuart C. Shapiro Professor, CSE Director, SNePS Research Group Member, Center for Cognitive Science Fellow, AAAI Chair, ACM/SIGART, President, KR., Inc.,

S.C. Shapiro Introduction

S.C. Shapiro Long-Term Goal Theory and Implementation of Natural-Language-Competent Computerized Cognitive Agent and Supporting Research in Artificial Intelligence Cognitive Science Computational Linguistics.

S.C. Shapiro Research Areas Knowledge Representation and Reasoning Cognitive Robotics Natural-Language Understanding Natural-Language Generation.

S.C. Shapiro Goal A computational cognitive agent that can: –Understand and communicate in English; –Discuss specific, generic, and “rule-like” information; –Reason; –Discuss acts and plans; –Sense; –Act; –Remember and report what it has sensed and done.

S.C. Shapiro Cassie A computational cognitive agent –Embodied in hardware –or Software-Simulated –Based on SNePS and GLAIR.

S.C. Shapiro GLAIR Architecture Knowledge Level Perceptuo-Motor Level Sensory-Actuator Level NL Vision Sonar Motion Proprioception Grounded Layered Architecture with Integrated Reasoning SNePS

S.C. Shapiro SNePS Knowledge Representation and Reasoning –Propositions as Terms SNIP: SNePS Inference Package –Specialized connectives and quantifiers SNeBR: SNePS Belief Revision SNeRE: SNePS Rational Engine Interface Languages –SNePSUL: Lisp-Like –SNePSLOG: Logic-Like –GATN for Fragments of English.

S.C. Shapiro Interaction with Cassie English (Statement, Question, Command) (Current) Set of Beliefs [SNePS] (Updated) Set of Beliefs [SNePS] Actions [SNeRE] (New Belief) [SNePS] English sentence expressing new belief answering question reporting actions Answer [SNIP] GATN Parser GATN Generator Reasoning Clarification Dialogue Looking in World Reasoning

S.C. Shapiro Example Cassies & Worlds

S.C. Shapiro Cassie, the BlocksWorld Robot

S.C. Shapiro FEVAHR: Award-Winning Embodied Cassie Project

S.C. Shapiro FEVAHRWorld Simulation

S.C. Shapiro UXO Remediation Cassie Cassie Corner flag NonUXO object Corner flag UXO Battery meter Corner flag Drop-off zone Field Safe zone Recharging Station

S.C. Shapiro Crystal Space Environment

S.C. Shapiro UB Virtual Site Museum The 9 th -Century BC Northwest Palace at Nimrud-Iraq is the best preserved and documented of all the Assyrian palaces. Its audience halls were originally created as the backdrop for differing royal activities. Completely immersive re-creation of this palace with animated characters and interactive story boards. T. Kesavadas & S. Paley Modeling of King - Animation in Real time VR

S.C. Shapiro Sample Research Issues Intensional Entities

S.C. Shapiro Intensional Entities 1 Rather than represent “objects in the world,” represent mental entities. Includes Imaginary and Fictional Entities. Multiple mental entities may correspond to one world object. –Intensional entities may be co-extensional. –But must be kept separate.

S.C. Shapiro Intensional Entities 2 : The morning star is the evening star. I understand that the morning star is the evening star. : The evening star is Venus. I understand that Venus is the evening star. : Clark Kent is Superman. I understand that Superman is Clark Kent.

S.C. Shapiro Intensional Entities 3 : Lois Lane saw Clark Kent. I understand that Lois Lane saw Clark Kent. : Did Lois Lane see Superman? I don't know. : Did Lois Lane see Clark Kent? Yes, Lois Lane saw Clark Kent. Note Open World Assumption.

S.C. Shapiro Intensional Entities 4 : Superman went to the morning star. I understand that Superman went to Venus. : Did Clark Kent go to Venus? Yes, Superman went to Venus.

S.C. Shapiro Intensional Entities 5 : Buck Rogers went to the evening star. I understand that Buck Rogers went to Venus. : Who went to Venus? Buck Rogers went to Venus and Superman went to Venus.

S.C. Shapiro Intensional Entities 6 The morning star The evening star Venus Superman Clark Kent Buck Rogers Lois Lane Go to See

S.C. Shapiro Sample Research Issues Complex Categories

S.C. Shapiro Complex Categories 1 Noun Phrases: {N | Adj}* N Understanding of the modification must be left to reasoning. Example: orange juice seat Representation must be left vague.

S.C. Shapiro : Kevin went to the orange juice seat. I understand that Kevin went to the orange juice seat. : Did Kevin go to a seat? Yes, Kevin went to the orange juice seat. Complex Categories 2

S.C. Shapiro : Pat is an excellent teacher. I understand that Pat is an excellent teacher. : Is Pat a teacher? Yes, Pat is a teacher. : Lucy is a former teacher. I understand that Lucy is a former teacher. Complex Categories 3

S.C. Shapiro : `former' is a negative adjective. I understand that `former' is a negative adjective. : Is Lucy a teacher? No, Lucy is not a teacher. Complex Categories 4

S.C. Shapiro PseudoRepresentation of Complex Categories Isa(B30, CompCat(orange, CompCat(juice, seat))) Isa(Pat, CompCat(excellent, teacher)) Isa(Lucy, CompCat(former, teacher))

S.C. Shapiro Sample Research Issues Possession

S.C. Shapiro Possession 1 “One man’s meat is another man’s poison.”

S.C. Shapiro : Richard's meat is Henry's poison. I understand that Henry's poison is Richard's meat. : Edward ate Richard's meat. I understand that Edward ate Richard's meat. : Did Edward eat Henry's poison? Yes, Edward ate Henry's poison. Possession 2

S.C. Shapiro : Did Edward eat Henry’s meat? I don’t know. : Did Edward eat Richard's poison? I don’t know. Possession 3 Moral: Possession is a three-place relation.

S.C. Shapiro PseudoRepresentation of Possession Has(Richard, meat, B35) Has(Henry, poison, B37) Equiv(B35, B37)

S.C. Shapiro Sample Research Issues Propositions about Propositions

S.C. Shapiro Propositions about Propositions 1 Propositions are “first-class” mental entities. They can be discussed, just like other mental entities. And must be represented like other mental entities.

S.C. Shapiro : That Bill is sweet is Mary's favorite proposition. I understand that Mary's favorite proposition is that Bill is sweet. : Mike believes Mary's favorite proposition. I understand that Mike believes that Bill is sweet. Propositions about Propositions 2

S.C. Shapiro : That Mary's favorite proposition is that Bill is sweet is cute. I understand that that Mary's favorite proposition is that Bill is sweet is cute. Propositions about Propositions 3

S.C. Shapiro Representing Propositions Representation of Proposition –Not by a Logical Sentence –But by a Functional Term –Denoting a Proposition.

S.C. Shapiro PseudoRepresentation of Propositions about Propositions Has(Mary, CompCat(favorite, proposition), HasProp(Bill, sweet)) Believes(Mike, HasProp(Bill, sweet)) HasProp(Has(Mary, CompCat(favorite, proposition), HasProp(Bill, sweet)), cute)

S.C. Shapiro Sample Research Issues Conditional Plans

S.C. Shapiro Conditional Plans If a block is on a support then a plan to achieve that the support is clear is to pick up the block and then put the block on the table. all(x, y) ({Block(x), Support(y), On(x, y)} &=> {GoalPlan(Clear(y), Snsequence(Pickup(x), Put(x, Table)))}) STRIPS-like representation: No times

S.C. Shapiro Use of Conditional Plan GoalPlan(Clear(B), Snsequence(Pickup(A), Put(A, Table))) Remember (cache) derived propositions.

S.C. Shapiro Use of Conditional Plan GoalPlan(Clear(B), Snsequence(Pickup(A), Put(A, Table))) ??? SNeBR to the rescue!

S.C. Shapiro Sample Research Issues Indexicals

S.C. Shapiro Representation and Use of Indexicals Words whose meanings are determined by occasion of use E.g. I, you, now, then, here, there Deictic Center *I : SNePS term representing Cassie *YOU: person Cassie is talking with *NOW: current time.

S.C. Shapiro Analysis of Indexicals (in input) First person pronouns: *YOU Second person pronouns: *I “here”: location of *YOU Present/Past relative to *NOW.

S.C. Shapiro Generation of Indexicals *I : First person pronouns *YOU : Second person pronouns *NOW : used to determine tense and aspect.

S.C. Shapiro Come here. Use of Indexicals 1

S.C. Shapiro Come here. I came to you, Stu. I am near you. Use of Indexicals 2

S.C. Shapiro Who am I? Your name is ‘Stu’ and you are a person. Who have you talked to? I am talking to you. Talk to Bill. I am talking to you, Bill. Come here. Use of Indexicals 3

S.C. Shapiro Come here. I found you. I am looking at you. Use of Indexicals 4

S.C. Shapiro Come here. I came to you. I am near you. I found you. I am looking at you. Use of Indexicals 5

S.C. Shapiro Who am I? I talked to Stu and I am talking to you. Your name is ‘Bill’ and you are a person. Who are you? I am the FEVAHR and my name is ‘Cassie’. Who have you talked to? Use of Indexicals 6

S.C. Shapiro Sample Research Issues Time

S.C. Shapiro Motivating Joke 9:30:00 AM (Door-to-Door Salesman): May I interest you in a brush? 9:30:02 AM (Homeowner): Not now. 9:30:03 AM (Salesman): Now?

S.C. Shapiro A Personal Sense of Time *NOW contains SNePS term representing current time. *NOW moves when Cassie acts or perceives a change of state.

S.C. Shapiro The Pacemaker PML process periodically increments variable COUNT. *COUNT = some PML integer. Reset to 0 when NOW moves. Provides bodily “feel” of passing time.

S.C. Shapiro Quantizing Time Cannot conceptualize fine distinctions in time intervals. So quantize, e.g. into half orders of magnitude (Hobbs, 2000).

S.C. Shapiro Movement of Time with Pacemaker NOW COUNTn hom 0 KL PML t1 t2 q ! beforeafter time duration !

S.C. Shapiro The Vagueness of “now” I’m now giving a talk. I’m now on sabbatical. I’m now living in East Amherst. I’m now at UB. Multiple now’s at different granularities.

S.C. Shapiro NOW-MTF NOW Semi-lattice of times, all of which contain *NOW, any of which could be meant by “now” Finite---only conceptualized times of conceptualized states Maximal Temporal Frame based on *NOW

S.C. Shapiro Moving NOW with MTF NOW

S.C. Shapiro Current

S.C. Shapiro Current Students Bharat Bhushan, M.S. Candidate Preferential Ordering of Beliefs for Default Reasoning Debra T. Burhans, Ph.D. Candidate A Question-Answering Interpretation of Resolution Refutation Frances L. Johnson, Ph.D. Candidate Belief Revision in a Deductively Open Belief Space John F. Santore, Ph.D. Candidate Distinguishing Perceptually Indistinguishable Objects

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