Research in Knowledge Representation, Reasoning, and Acting Stuart C. Shapiro Professor, CSE Director, Center for Cognitive Science Director,

Slides:

Advertisements

Similar presentations

An F-Measure for Context-Based Information Retrieval Michael Kandefer and Stuart C. Shapiro University at Buffalo Department of Computer Science and Engineering.

Advertisements

SPECIFYING MODALITIES IN THE MGLAIR ARCHITECTURE Stuart C. Shapiro and Jonathan P. Bona Department of Computer Science and Engineering And Center for Cognitive.

S.C. Shapiro Knowledge Representation and Reasoning Stuart C. Shapiro Professor, CSE Director, SNePS Research Group Member, Center for Cognitive.

Research in Knowledge Representation and Reasoning Stuart C. Shapiro Department of Computer Science & Engineering Center for MultiSource Information.

3/30/00 Agents that Reason Logically by Chris Horn Jiansui Yang Xiaojing Wu.

Artificial Intelligence Knowledge-based Agents Russell and Norvig, Ch. 6, 7.

The GLAIR Architecture for Cognitive Robotics Stuart C. Shapiro Department of Computer Science & Engineering and Center for Cognitive Science.

The GLAIR Cognitive Architecture and Prospects for Consciousness Stuart C. Shapiro Department of Computer Science & Engineering and Center.

A Categorization of Contextual Constraints Michael Kandefer and Stuart C. Shapiro University at Buffalo Department of Computer Science and Engineering.

The GLAIR Cognitive Architecture Stuart C. Shapiro and Jonathan P. Bona Department of Computer Science & Engineering Center for Cognitive Science.

The GLAIR Architecture for Cognitive Robots Stuart C. Shapiro Department of Computer Science & Engineering and Center for Cognitive Science.

Knowledge Representation for Self-Aware Computer Systems Stuart C. Shapiro Department of Computer Science and Engineering, and Center for Cognitive.

S.C. Shapiro Development of a Cognitive Agent Stuart C. Shapiro Department of Computer Science and Engineering and Center for Cognitive Science.

S.C. Shapiro Endowing Agents with a Personal Sense of Time Haythem O. Ismail & Stuart C. Shapiro Department of Computer Science and Engineering.

S.C. Shapiro Knowledge Representation for Natural Language Competence Stuart C. Shapiro Department of Computer Science and Engineering and.

Cassie as a Self-Aware SNePS/GLAIR Agent Stuart C. Shapiro Department of Computer Science and Engineering, and Center for Cognitive Science.

Artificial Intelligence and Lisp Lecture 13 Additional Topics in Artificial Intelligence LiU Course TDDC65 Autumn Semester, 2010

Research in Knowledge Representation, Reasoning, and Acting Stuart C. Shapiro Professor, CSE Affiliated Professor, Linguistics, Philosophy.

Logical Agents Chapter 7. Why Do We Need Logic? Problem-solving agents were very inflexible: hard code every possible state. Search is almost always exponential.

Computing & Information Sciences Kansas State University Lecture 11 of 42 CIS 530 / 730 Artificial Intelligence Lecture 11 of 42 William H. Hsu Department.

Logical Agents Chapter 7. Why Do We Need Logic? Problem-solving agents were very inflexible: hard code every possible state. Search is almost always exponential.

S.C. Shapiro Knowledge Representation and Reasoning Stuart C. Shapiro Professor, CSE Director, SNePS Research Group Member, Center for Cognitive.

Knowledge in intelligent systems So far, we’ve used relatively specialized, naïve agents. How can we build agents that incorporate knowledge and a memory?

COMP 4640 Intelligent & Interactive Systems Cheryl Seals, Ph.D. Computer Science & Software Engineering Auburn University.

S.C. Shapiro An Intelligent Interface to a GIS Stuart C. Shapiro Professor, CSE Director, SNePS Research Group Member, Center for Cognitive.

Semantics of a Propositional Network Stuart C. Shapiro Department of Computer Science & Engineering Center for MultiSource Information Fusion.

© Franz Kurfess Lab Exercise Reasoning CSC 480: Artificial Intelligence Wumpus World Lab Dr. Franz J. Kurfess Computer Science Department Cal Poly.

CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin.

S.C. Shapiro Symbol-Anchoring in Cassie Stuart C. Shapiro and Haythem O. Ismail Department of Computer Science and Engineering and Center for.

© 2002 Franz J. Kurfess Introduction 1 CPE/CSC 481: Knowledge-Based Systems Dr. Franz J. Kurfess Computer Science Department Cal Poly.

A Logic of Arbitrary and Indefinite Objects Stuart C. Shapiro Department of Computer Science and Engineering, and Center for Cognitive Science.

Knowledge Acquisition by an Intelligent Acting Agent Michael Kandefer and Stuart Shapiro Department of Computer Science and Engineering, Center for Cognitive.

S.C. Shapiro Knowledge Representation and Reasoning Stuart C. Shapiro Professor, CSE Director, SNePS Research Group Member, Center for Cognitive.

S.C. Shapiro Symbol Anchoring in a Grounded Layered Architecture with Integrated Reasoning Stuart C. Shapiro Department of Computer Science.

Improving Recovery for Belief Bases Frances L. Johnson & Stuart C. Shapiro Department of Computer Science and Engineering, Center for Multisource.

Angel: Interactive Computer Graphics 4E © Addison-Wesley 2005 Sampling and Aliasing Ed Angel Professor of Computer Science, Electrical and Computer Engineering,

AI: Trends and Directions Stuart C. Shapiro Professor, CSE Affiliated Professor, Linguistics, Philosophy Director, SNePS Research Group ACM.

Research in Knowledge Representation, Reasoning, and Acting Stuart C. Shapiro Professor, CSE Affiliated Professor, Linguistics, Philosophy.

Perpetual Self-aware Cognitive Agents Michael T. Cox BBNT Cambridge.

S.C. Shapiro An Introduction to SNePS 3 Stuart C. Shapiro Department of Computer Science and Engineering and Center for Cognitive Science State.

Artificial Intelligence Lecture No. 9 Dr. Asad Ali Safi Assistant Professor, Department of Computer Science, COMSATS Institute of Information Technology.

CSE4/563: Knowledge Representation Recitation September 13, 2010 “Intelligence is the art of good guesswork.” –H.B. Barlow.

Inference Graphs: A Roadmap Daniel R. Schlegel and Stuart C. Department of Computer Science and Engineering L A – Logic of Arbitrary.

Artificial Intelligence And Machine learning. Drag picture to placeholder or click icon to add What is AI?

COMMONWEALTH OF AUSTRALIA Copyright Regulations 1969 WARNING This material has been reproduced and communicated to you by or on behalf of Monash University.

1 Logical Agents CS 171/271 (Chapter 7) Some text and images in these slides were drawn from Russel & Norvig’s published material.

Concurrent Inference Graphs Daniel R. Schlegel Department of Computer Science and Engineering Problem Summary Inference graphs 2 in their current form.

1 Knowledge Representation Propositional Logic Vumpus World Knowledge Representation Propositional Logic Vumpus World.

1 Logical Agents CS 171/271 (Chapter 7) Some text and images in these slides were drawn from Russel & Norvig’s published material.

The SNePS Research Group Semantic Network Processing System The long-term goal of The SNePS Research Group is the design and construction of a natural-language-using.

Knowledge Representation and Reasoning in SNePS for Bioinformatics Stuart C. Shapiro Department of Computer Science and Engineering, and Center.

1 The Wumpus Game StenchBreeze Stench Gold Breeze StenchBreeze Start  Breeze.

ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information.

W. L. Johnson and J. T Rickel. “Animated Pedagogical Agents: Face-to-Face Interaction in Interactive Learning Environments,” International Journal of Artificial.

Ch. 7 – Logical Agents Supplemental slides for CSE 327 Prof. Jeff Heflin.

1 UNIT-3 KNOWLEDGE REPRESENTATION. 2 Agents that reason logically(Logical agents) A Knowledge based Agent The Wumpus world environment Representation,

COMP 4640 Intelligent & Interactive Systems Cheryl Seals, Ph.D. Computer Science & Software Engineering Auburn University.

1 Knowledge Representation Logic and Inference Propositional Logic Vumpus World Knowledge Representation Logic and Inference Propositional Logic Vumpus.

Artificial Intelligence Logical Agents Chapter 7.

UNIVERSITY OF SOUTH CAROLINA Department of Computer Science and Engineering CSCE 781 Knowledge Systems: Student Presentations Spring 2011 Marco Valtorta.

Artificial Intelligence and Lisp Lecture 13 Additional Topics in Artificial Intelligence LiU Course TDDC65 Autumn Semester,

Interdisciplinary research on language & speech

COMP 4640 Intelligent & Interactive Systems

MGLAIR Modal Grounded Layered Architecture with Integrated Reasoning

CSE 4705 Artificial Intelligence

MGLAIR Modal Grounded Layered Architecture with Integrated Reasoning

Knowledge Representation I (Propositional Logic)

Institute of Computing Technology

CMSC 471 Fall 2011 Class #10 Tuesday, October 4 Knowledge-Based Agents

Logical Agents Prof. Dr. Widodo Budiharto 2018

Presentation transcript:

Research in Knowledge Representation, Reasoning, and Acting Stuart C. Shapiro Professor, CSE Director, Center for Cognitive Science Director, SNePS Research Group Faculty Member, Interdisciplinary MS in Computational Linguistics Fellow, AAAI

Research OverviewS. C. Shapiro2 Long-Term Goal Theory and Implementation of Natural-Language-Competent Computerized Cognitive Agent/Robot and Supporting Research in Artificial Intelligence Cognitive Science Computational Linguistics.

Research OverviewS. C. Shapiro3 Cassie A computational cognitive agent –Embodied in hardware –or Software-Simulated –Based on SNePS and GLAIR.

Research OverviewS. C. Shapiro4 Cassie as a Wumpus World Agent From: Stuart C. Shapiro and Michael Kandefer, A SNePS Approach to The Wumpus World Agent or Cassie Meets the Wumpus. In Leora Morgenstern and Maurice Pagnucco, Eds., IJCAI-05 Workshop on Nonmonotonic Reasoning, Action, and Change (NRAC'05): Working Notes, IJCAII, Edinburgh, 2005, A SNePS Approach to The Wumpus World Agent or Cassie Meets the Wumpus

Research OverviewS. C. Shapiro5 : perform get(gold) No breeze here. No stench here. Exploring the cave... Found a safe room...

Research OverviewS. C. Shapiro6 I am in room (1, 0), facing east No breeze here. No stench here. Exploring the cave... Found a safe room...

Research OverviewS. C. Shapiro7

Research OverviewS. C. Shapiro8 I am in room (1, 1), facing south I feel a breeze. No stench here. Exploring the cave... Found a safe room...

Research OverviewS. C. Shapiro9

Research OverviewS. C. Shapiro10 I am in room (0, 1), facing west No breeze here. No stench here. Exploring the cave... Found a safe room...

Research OverviewS. C. Shapiro11

Research OverviewS. C. Shapiro12 I am in room (0, 2), facing south I feel a breeze. No stench here. Exploring the cave... Visiting an old room... This is boring.

Research OverviewS. C. Shapiro13

Research OverviewS. C. Shapiro14 Exploring the cave... Visiting an old room... This is boring.

Research OverviewS. C. Shapiro15 Exploring the cave... Visiting an old room... This is boring.

Research OverviewS. C. Shapiro16

Research OverviewS. C. Shapiro17 Exploring the cave... Found a safe room...

Research OverviewS. C. Shapiro18 I am in room (2, 0), facing east I feel a breeze. No stench here. Exploring the cave... Visiting an old room... This is boring.

Research OverviewS. C. Shapiro19

Research OverviewS. C. Shapiro20 Exploring the cave... Visiting an old room... This is boring.

Research OverviewS. C. Shapiro21 Exploring the cave... Visiting an old room... This is boring.

Research OverviewS. C. Shapiro22

Research OverviewS. C. Shapiro23 Exploring the cave... Visiting an old room... This is boring.

Research OverviewS. C. Shapiro24

Research OverviewS. C. Shapiro25 Exploring the cave... I'll chance a move...

Research OverviewS. C. Shapiro26 I am in room (1, 2), facing south No breeze here. I'm grabbing for the gold. No stench here. I'm going home!

Research OverviewS. C. Shapiro27

Research OverviewS. C. Shapiro28

Research OverviewS. C. Shapiro29

Research OverviewS. C. Shapiro30

Research OverviewS. C. Shapiro31 Score = 966.

Research OverviewS. C. Shapiro32 Important SNePS Features 1 First-person beliefs –Not third-person “truth” about agent or world Beliefs are current beliefs –Even if about the past On-line acting Reified propositions as well as acts & … Neither states nor times are privileged

Research OverviewS. C. Shapiro33 Important SNePS Features 2 SNeRE acts with operational semantics –External acts: go(right) do(grab) senseFor(breeze) –Control acts: snsequence(go(right), go(right)) –Mental acts: believe(p) disbelieve(p)

Research OverviewS. C. Shapiro34 Important SNePS Features 3 SNeRE policies integrate reasoning & acting –whendo(See(glitter), do(grab)) –ActPlan(find(home), snif({if(In(cell(0,0)), do(stop)), else(…)}))

Research OverviewS. C. Shapiro35 Important SNePS Features 4 Use of SNePS andor connective and belief revision for state constraints: andor(1,1){Facing(north), Facing(south), Facing(east), Facing(west)} Facing(east) => ~Facing(north), ~Facing(south), ~Facing(west) believe(Facing(south)) Facing(south), ~Facing(north), ~Facing(east), ~Facing(west)

Research OverviewS. C. Shapiro36 Important SNePS Features 5 Nondeterministic Choice ~Have(gold) =>(all(r1)(In(r1) => ActPlan(explore(cave), withsome({?r2, ?d1}, SafeNewRoom(r1, ?r2, ?d1), snsequence3(turn(?d1), move(forward), believe(Bored(0))), ))))

Research OverviewS. C. Shapiro37 Important SNePS Features 6 Numerical Quantifier wheneverdo(Feel(breeze), withsome/3(?r, In(?r), believe(nexists(1,4,4)(c)({Adjacent(?r,c)}: {Contains(c,pit)}))))

Research OverviewS. C. Shapiro38 Agents in a Virtual Reality Drama Stuart C. Shapiro, Josephine Anstey, David E. Pape, Trupti Devdas Nayak, Michael Kandefer, & Orkan Telhan, The Trial The Trail, Act 3: A Virtual Reality Drama Using Intelligent Agents. In R. Michael Young & John Laird, Eds., Proceedings of the First Annual Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE-05), AAAI Press, Menlo Park, CA, 2005, The Trial The Trail, Act 3: A Virtual Reality Drama Using Intelligent AgentsArtificial Intelligence and Interactive Digital Entertainment(AIIDE-05)AAAI Press Stuart C. Shapiro, Josephine Anstey, David E. Pape, Trupti Devdas Nayak, Michael Kandefer, & Orkan Telhan, MGLAIR Agents in Virtual and other Graphical Environments, Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05), AAAI Press, Menlo Park, CA, 2005, MGLAIR Agents in Virtual and other Graphical EnvironmentsAAAI Press

Research OverviewS. C. Shapiro39 Bad guy agents hassling a human participant SNePS Multi-Agents

Research OverviewS. C. Shapiro40 Reconsideration Frances L Johnson and Stuart C. Shapiro, Dependency-Directed Reconsideration: Belief Base Optimization for Truth Maintenance Systems, Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05), AAAI Press, Menlo Park, CA, 2005,

Research OverviewS. C. Shapiro41 Reconsideration Example KB1s, d Add and make consistent  (s  d)s  d KB2  (s  d)s, d, s  d Add and make consistent s  d  (s  d) KB3 s  ds, d, s  d Credibility order: s  d >  (s  d) > s > d

Research OverviewS. C. Shapiro42 p ~q pqpq ~v w m ~r pvpv prpr mrmr {p,p  q,~q} {w  v,w,~v} {m  r,~r,m} s ~t n stst {s,s  t,~t} {p,p  r,~r} {p,p  v,~v} wvwv DDR Graph ~p {~p,p} {p,p  q,~q} ~q {p,p  r,~r} ~r {~p,p} {p,p  v,~v} ~v

Research OverviewS. C. Shapiro43 For More Information Shapiro: SNePS Research Group: –Meets Tuesdays 9-11, 45 Baldy Hall –Join us!