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Commonsense Reasoning: An Event Calculus Based Approach 2nd edition [Mīkstie vāki]

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(IBM Watson Group and IBM Research, New York, USA)
  • Formāts: Paperback / softback, 516 pages, height x width: 235x191 mm, weight: 950 g
  • Izdošanas datums: 23-Oct-2014
  • Izdevniecība: Morgan Kaufmann Publishers In
  • ISBN-10: 0128014164
  • ISBN-13: 9780128014165
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Commonsense Reasoning: An Event Calculus Based Approach 2nd editionPalielināt
  • Formāts: Paperback / softback, 516 pages, height x width: 235x191 mm, weight: 950 g
  • Izdošanas datums: 23-Oct-2014
  • Izdevniecība: Morgan Kaufmann Publishers In
  • ISBN-10: 0128014164
  • ISBN-13: 9780128014165
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9780128014165.html
Keywords:

To endow computers with common sense is one of the major long-term goals of artificial intelligence research. One approach to this problem is to formalize commonsense reasoning using mathematical logic.Commonsense Reasoning: An Event Calculus Based Approach is a detailed, high-level reference on logic-based commonsense reasoning. It uses the event calculus, a highly powerful and usable tool for commonsense reasoning, which Erik Mueller demonstrates as the most effective tool for the broadest range of applications. He provides an up-to-date work promoting the use of the event calculus for commonsense reasoning, and bringing into one place information scattered across many books and papers. Mueller shares the knowledge gained in using the event calculus and extends the literature with detailed event calculus solutions that span many areas of the commonsense world.

The Second Edition features new chapters on commonsense reasoning using unstructured information including the Watson system, commonsense reasoning using answer set programming, and techniques for acquisition of commonsense knowledge including crowdsourcing.

Drawing upon years of practical experience and using numerous examples and illustrative applications Erik Mueller shows you the keys to mastering commonsense reasoning. You’ll be able to:

  • Understand techniques for automated commonsense reasoning
  • Incorporate commonsense reasoning into software solutions
  • Acquire a broad understanding of the field of commonsense reasoning.
  • Gain comprehensive knowledge of the human capacity for commonsense reasoning

Papildus informācija

This second edition pushes the boundaries of artificial intelligence and allows computer systems to be more aware of the human world, more flexible in the face of surprises, and more responsive to human needs.
Praise for Commonsense Reasoning xvii
Foreword to the First Edition xix
Preface xxi
About the Author xxvii
Acknowledgments to the First Edition xxix
Acknowledgments to the Second Edition xxxi
New to the Second Edition xxxiii
Chapter 1 Introduction
1(18)
1.1 What is Commonsense Reasoning?
1(1)
1.2 Key Issues of Commonsense Reasoning
2(5)
1.2.1 Summary
6(1)
1.3 Brief History of Commonsense Reasoning
7(2)
1.3.1 Logical Methods
7(1)
1.3.2 Nonlogical Methods
8(1)
1.4 The Event Calculus
9(3)
1.4.1 Events, Fluents, and Timepoints
9(1)
1.4.2 A Simple Example
10(1)
1.4.3 Automated Event Calculus Reasoning
11(1)
Bibliographic Notes
12(7)
Part I Foundations
Chapter 2 The Event Calculus
19(30)
2.1 First-Order Logic
19(3)
2.1.1 Syntax of First-Order Logic
19(1)
2.1.2 Semantics of First-Order Logic
20(1)
2.1.3 Proof Theory
20(1)
2.1.4 Many-Sorted First-Order Logic
20(1)
2.1.5 Notational Conventions
21(1)
2.2 Event Calculus Basics
22(1)
2.2.1 Event Calculus Sorts
22(1)
2.2.2 Event Calculus Predicates
22(1)
2.2.3 States of a Fluent
23(1)
2.3 Event Calculus Axiomatizations
23(5)
2.3.1 EC
23(3)
2.3.2 DEC
26(1)
2.3.3 Choosing Between EC and DEC
27(1)
2.4 Reification
28(1)
2.4.1 Unique Names Axioms
29(1)
2.5 Conditions
29(1)
2.6 Circumscription
30(2)
2.6.1 Computing Circumscription
31(1)
2.6.2 Example: Circumscription of Happens
31(1)
2.6.3 Example: Circumscription of Initiates
32(1)
2.7 Domain Descriptions
32(5)
2.7.1 Example: Sleep
34(2)
2.7.2 Inconsistency
36(1)
2.8 Reasoning Types
37(2)
2.8.1 Deduction and Temporal Projection
37(1)
2.8.2 Abduction and Planning
37(1)
2.8.3 Example: Sleep Abduction
37(1)
2.8.4 Postdiction
38(1)
2.8.5 Model Finding
39(1)
Bibliographic Notes
39(7)
Exercises
46(3)
Part II Commonsense Phenomena
Chapter 3 The Effects of Events
49(18)
3.1 Positive and Negative Effect Axioms
49(7)
3.1.1 Example: Telephone
50(6)
3.2 Effect Axiom Idioms
56(1)
3.3 Preconditions
57(2)
3.3.1 Fluent Preconditions
58(1)
3.3.2 Action Preconditions
58(1)
3.3.3 Example: Walking Through a Door
59(1)
3.4 State Constraints
59(3)
3.4.1 Example: Telephone Revisited
61(1)
Bibliographic Notes
62(3)
Exercises
65(2)
Chapter 4 The Triggering of Events
67(10)
4.1 Trigger Axioms
67(3)
4.1.1 Example: Alarm Clock
67(3)
4.2 Preventing Repeated Triggering
70(4)
4.2.1 Example: Bank Account Service Fee
70(4)
4.3 Triggered Fluents
74(1)
Bibliographic Notes
74(1)
Exercises
75(2)
Chapter 5 The Commonsense Law of Inertia
77(14)
5.1 Representation of the Commonsense Law of Inertia
77(4)
5.1.1 Frame Problem
77(1)
5.1.2 Classical Frame Axioms
78(1)
5.1.3 Explanation Closure Axioms
78(1)
5.1.4 Minimizing Event Occurrences
79(1)
5.1.5 Introduction of Initiates Predicate
79(1)
5.1.6 Minimizing Event Effects
80(1)
5.1.7 Introduction of Terminates Predicate
80(1)
5.1.8 Discussion
80(1)
5.2 Representing Release from the Commonsense Law of Inertia
81(4)
5.2.1 Example: Yale Shooting Scenario
81(1)
5.2.2 Releasing from Inertia
82(1)
5.2.3 Restoring Inertia
83(1)
5.2.4 Explanation Closure Axioms for ReleasedAt
83(1)
5.2.5 Example: Russian Turkey Scenario
84(1)
5.3 Release Axioms
85(1)
Bibliographic Notes
86(3)
Exercises
89(2)
Chapter 6 Indirect Effects of Events
91(26)
6.1 Effect Axioms
91(3)
6.1.1 Example: Carrying a Book
91(3)
6.1.2 Discussion
94(1)
6.2 Primitive and Derived Fluents
94(2)
6.2.1 Example: Device
94(2)
6.3 Release Axioms and State Constraints
96(2)
6.3.1 Example: Carrying a Book Revisited
96(2)
6.4 Effect Constraints
98(1)
6.4.1 Example: Carrying a Book Revisited
99(1)
6.5 Causal Constraints
99(6)
6.5.1 Example: Thielscher's Circuit
102(3)
6.6 Trigger Axioms
105(6)
6.6.1 Example: Thielscher's Circuit with Delays
105(2)
6.6.2 Example: Shanahan's Circuit with Delays
107(4)
Bibliographic Notes
111(4)
Exercises
115(2)
Chapter 7 Continuous Change
117(10)
7.1 Trajectory Axioms
117(4)
7.1.1 Example: Falling Object
117(1)
7.1.2 Example: Falling Object with Events
118(3)
7.1.3 Introduction of Trajectory Predicate
121(1)
7.2 AntiTrajectory Axioms
121(2)
7.2.1 Example: Hot Air Balloon
122(1)
7.3 Using AntiTrajectory Instead of Releases
123(2)
7.3.1 Example: Falling Object with AntiTrajectory
123(2)
Bibliographic Notes
125(1)
Exercises
126(1)
Chapter 8 Concurrent Events
127(12)
8.1 Restricting Concurrency
127(2)
8.1.1 State Constraints
127(1)
8.1.2 Event Occurrence Constraints
128(1)
8.1.3 Discussion
129(1)
8.2 Cumulative and Canceling Effects
129(5)
8.2.1 Example: Camera with Flash
130(1)
8.2.2 Example: Moving Robot
131(3)
Bibliographic Notes
134(2)
Exercises
136(3)
Chapter 9 Nondeterministic Effects of Events
139(8)
9.1 Determining Fluents
139(3)
9.1.1 Example: Roulette Wheel
139(3)
9.2 Disjunctive Event Axioms
142(1)
9.2.1 Example: Running and Driving
142(1)
Bibliographic Notes
143(1)
Exercises
144(3)
Part III Commonsense Domains
Chapter 10 Space
147(20)
10.1 Relational Space
147(6)
10.1.1 Basic Representation
147(1)
10.1.2 Extended Representation
148(2)
10.1.3 Example: Moving a Newspaper and a Box
150(3)
10.2 Metric Space
153(7)
10.2.1 Example: Two Baseballs Colliding
154(6)
10.3 Object Identity
160(3)
10.3.1 Example: One Screen
160(2)
10.3.2 Example: Two Screens
162(1)
Bibliographic Notes
163(1)
Exercises
164(3)
Chapter 11 The Mental States of Agents
167(38)
11.1 Beliefs, Goals, and Plans
167(17)
11.1.1 Reactive Behavior
167(1)
11.1.2 Goal-Driven Behavior
167(1)
11.1.3 Formalization
168(2)
11.1.4 Example: Hungry Cat Scenario
170(14)
11.2 Emotions
184(11)
11.2.1 Emotion Theory
184(1)
11.2.2 Formalization
185(8)
11.2.3 Example: Lottery
193(2)
11.3 The Epistemic Functional Event Calculus
195(4)
11.3.1 FEC Basics
196(1)
11.3.2 FEC Axiomatization
196(1)
11.3.3 EFEC Basics
197(1)
11.3.4 EFEC Axiomatization
197(2)
Bibliographic Notes
199(2)
Exercises
201(4)
Part IV Default Reasoning
Chapter 12 Default Reasoning
205(16)
12.1 Atemporal Default Reasoning
205(1)
12.2 Temporal Default Reasoning
206(1)
12.2.1 Event Occurrences
206(1)
12.2.2 Event Effects
207(1)
12.2.3 Using Minimized Events and Effects
207(1)
12.3 Default Reasoning Method
207(1)
12.4 Defaults and the Qualification Problem
208(3)
12.4.1 Example: Device Revisited
208(2)
12.4.2 Example: Broken Device
210(1)
12.4.3 Strong and Weak Qualifications
210(1)
12.4.4 Example: Erratic Device
210(1)
12.5 Default Events and Properties
211(1)
12.5.1 Default Events
211(1)
12.5.2 Default Properties
212(1)
Bibliographic Notes
212(4)
Exercises
216(5)
Part V Programs And Applications
Chapter 13 The Discrete Event Calculus Reasoner
221(12)
13.1 Discrete Event Calculus Reasoner Architecture
221(1)
13.2 Encoding Satisfiability Problems
221(1)
13.3 Simple Examples
222(4)
13.3.1 Deduction
222(1)
13.3.2 Abduction
223(1)
13.3.3 Postdiction
224(1)
13.3.4 Model Finding
225(1)
13.4 Example: Telephone
226(3)
13.5 Discrete Event Calculus Reasoner Language
229(1)
Bibliographic Notes
230(1)
Exercises
231(2)
Chapter 14 Applications
233(16)
14.1 Business Systems
233(7)
14.1.1 Payment Protocols
233(4)
14.1.2 Workflow Modeling
237(3)
14.2 Natural Language Understanding
240(4)
14.2.1 Story Understanding
240(4)
14.3 Vision
244(1)
Bibliographic Notes
245(1)
Exercises
246(3)
Chapter 15 Commonsense Reasoning Using Answer Set Programming
249(24)
15.1 Answer Set Programming
249(6)
15.1.1 Syntax of Answer Set Programs
251(1)
15.1.2 Semantics of Answer Set Programs
252(1)
15.1.3 Stable Models: Example 1
253(1)
15.1.4 Stable Models: Example 2
253(1)
15.1.5 Stable Models: Example 3
254(1)
15.1.6 Choice Rules
254(1)
15.2 Event Calculus in Answer Set Programming: Theory
255(6)
15.2.1 SM
256(1)
15.2.2 Relation Between SM and Stable Models
256(1)
15.2.3 Relation Between SM and Circumscription
257(1)
15.2.4 Use of SM for Event Calculus Reasoning
258(1)
15.2.5 EC2ASP
259(1)
15.2.6 Correctness of EC2ASP
260(1)
15.3 Event Calculus in Answer Set Programming: Practice
261(6)
15.3.1 Writing the Domain Description
261(1)
15.3.2 Running the Solver
262(2)
15.3.3 Example: Running and Driving
264(1)
15.3.4 Example: Carrying a Book
265(2)
15.4 F2LP
267(1)
15.5 E
267(1)
Bibliographic Notes
268(1)
Exercises
269(4)
Part VI Logical And Nonlogical Methods
Chapter 16 Logics for Commonsense Reasoning
273(24)
16.1 The Situation Calculus
273(3)
16.1.1 Relational and Functional Fluents
273(1)
16.1.2 Actions
273(1)
16.1.3 Action Effects
274(1)
16.1.4 Action Preconditions
275(1)
16.1.5 Equivalence of the Situation Calculus and the Event Calculus
275(1)
16.1.6 Discussion
275(1)
16.2 The Features and Fluents Framework
276(3)
16.2.1 Temporal Action Logics
276(3)
16.3 Action Languages
279(6)
16.3.1 C+
280(5)
16.4 The Fluent Calculus
285(2)
16.4.1 States
285(1)
16.4.2 Plus and Minus Macros
286(1)
16.4.3 State Update Axioms
286(1)
16.4.4 Nondeterministic Effects
286(1)
16.4.5 Concurrent Actions
286(1)
16.4.6 Discussion
287(1)
16.5 Discussion and Summary
287(2)
Bibliographic Notes
289(7)
Exercises
296(1)
Chapter 17 Nonlogical Methods for Commonsense Reasoning
297(18)
17.1 Qualitative Reasoning
297(1)
17.1.1 QSIM
297(1)
17.2 Analogical Processing
298(2)
17.2.1 Structure-Mapping Engine
298(2)
17.3 Probabilistic Reasoning
300(3)
17.3.1 Probability and Action
300(2)
17.3.2 Bayesian Networks
302(1)
17.4 Society of Mind
303(7)
17.4.1 ThoughtTreasure
304(2)
17.4.2 Polyscheme
306(2)
17.4.3 EM-ONE
308(2)
Bibliographic Notes
310(2)
Exercises
312(3)
Chapter 18 Commonsense Reasoning Using Unstructured Information
315(24)
18.1 Natural Language as a Programming Language
315(1)
18.1.1 SAFE
315(1)
18.1.2 OWL
316(1)
18.2 Reasoning with Restricted Natural Language
316(4)
18.2.1 Montagovian Syntax
317(1)
18.2.2 Attempto Controlled English
318(1)
18.2.3 PENG Light and the Event Calculus
319(1)
18.3 Reasoning Directly with Natural Language
320(1)
18.4 Watson
321(12)
18.4.1 Watson Architecture
321(1)
18.4.2 Question Analysis
322(1)
18.4.3 Primary Search
323(1)
18.4.4 Answer Lookup
324(1)
18.4.5 SKB
324(1)
18.4.6 Candidate Generation
324(1)
18.4.7 Supporting Evidence Retrieval
324(1)
18.4.8 Term Matching
325(1)
18.4.9 Term Weighting
326(1)
18.4.10 Answer Scoring
326(2)
18.4.11 Final Merging and Ranking
328(2)
18.4.12 WatsonPaths
330(1)
18.4.13 WatsonPaths for Commonsense Reasoning
331(1)
18.4.14 The AdaptWatson Methodology
332(1)
18.5 Comparison
333(1)
Bibliographic Notes
333(2)
Exercises
335(4)
Part VII Knowledge Acquisition
Chapter 19 Acquisition of Commonsense Knowledge
339(28)
19.1 Manual Acquisition of Commonsense Knowledge
339(5)
19.1.1 Cyc
339(2)
19.1.2 WordNet
341(1)
19.1.3 ThoughtTreasure
342(2)
19.2 Crowdsourcing Commonsense Knowledge
344(8)
19.2.1 Open Mind Common Sense
344(2)
19.2.2 Learner
346(2)
19.2.3 Open Mind Commons and ConceptNet
348(1)
19.2.4 AnalogySpace
349(3)
19.3 Games for Acquisition of Commonsense Knowledge
352(2)
19.3.1 ANIMAL
352(1)
19.3.2 Game for Interactive Open Mind Improvement
353(1)
19.3.3 Verbosity
353(1)
19.3.4 Common Consensus
353(1)
19.4 Mining Commonsense Knowledge
354
19.4.1 Mining Relation Instances From Text
354(1)
19.4.2 Mining Implicit Knowledge From Text
355
19.5 Event Calculus Reasoning Over Acquired Commonsense Knowledge
157(202)
19.6 Comparison of Acquisition Methods
359(1)
19.7 How Big is Human Common Sense?
360(1)
Bibliographic Notes
361(2)
Exercises
363(4)
Part VIII Conclusion
Chapter 20 Conclusion
367(6)
20.1 What Was Accomplished?
367(1)
20.1.1 What is the Event Calculus?
367(1)
20.1.2 How is the Event Calculus Used?
368(1)
20.2 Where is this Leading?
368(1)
20.3 Closing Remarks
369
Bibliographic Notes
169(204)
Part IX Appendices
Appendix A Logical Foundations
373(14)
A.1 Relations
373(1)
A.2 Inductive Definitions
374(1)
A.3 First-Order Logic
374(5)
A.3.1 Syntax of First-Order Logic
374(2)
A.3.2 Semantics of First-Order Logic
376(1)
A.3.3 Herbrand Structures and Models
377(1)
A.3.4 Proof Theory
377(2)
A.4 Many-Sorted First-Order Logic
379(2)
A.4.1 Syntax of Many-Sorted First-Order Logic
379(1)
A.4.2 Semantics of Many-Sorted First-Order Logic
380(1)
A.5 Second-Order Logic
381(1)
A.6 Datatypes
381(2)
A.6.1 Real Numbers
381(1)
A.6.2 Lists
382(1)
A.7 Circumscription
383(1)
A.7.1 Definition of Circumscription
383(1)
A.7.2 Example: Circumscription of P(A)
384(1)
A.7.3 Parallel Circumscription
384(1)
A.8 SM
384(1)
Bibliographic Notes
385(2)
Appendix B Equivalence of EC and DEC
387(6)
Appendix C Events with Duration
393(4)
Bibliographic Notes
395(2)
Appendix D The Discrete Event Calculus with Branching Time
397(12)
D.1 LDEC
397(1)
D.2 BDEC
398(2)
D.3 Relationship of BDEC and LDEC
400(2)
D.4 Relationship of BDEC and the Situation Calculus
402(5)
Bibliographic Notes
407(2)
Appendix E The Event Calculus and Temporal Action Logics
409(14)
E.1 The Event Calculus and TAL
409(5)
E.1.1 TALA Axiomatization
412(1)
E.1.2 ECA Axiomatization
413(1)
E.2 Lack of Equivalence Between TALA and ECA
414(1)
E.3 ECB Axiomatization
415(1)
E.4 Lack of Equivalence Between TALA and ECB
416(1)
E.5 General Action Type Specifications
417(1)
E.6 Restriction to Single-Step Actions
417(1)
E.7 Equivalence of TALAS and DECA
418(3)
E.8 Translation from TAL 1.0 L(ND) to L(FL)
421(2)
Appendix F Answers to Selected Exercises
423(6)
Chapter 2
423(1)
Chapter 3
423(1)
Chapter 4
424(1)
Chapter 5
424(2)
Chapter 6
426(1)
Chapter 8
427(2)
Bibliography 429(36)
Author Index 465(8)
Subject Index 473