Atnaujinkite slapukų nuostatas

El. knyga: Reasoning About Knowledge

  • Formatas: 536 pages
  • Išleidimo metai: 20-Jun-2019
  • Leidėjas: MIT Press
  • ISBN-13: 9780262256094
  • Formatas: 536 pages
  • Išleidimo metai: 20-Jun-2019
  • Leidėjas: MIT Press
  • ISBN-13: 9780262256094

DRM apribojimai

  • Kopijuoti:

    neleidžiama

  • Spausdinti:

    neleidžiama

  • El. knygos naudojimas:

    Skaitmeninių teisių valdymas (DRM)
    Leidykla pateikė šią knygą šifruota forma, o tai reiškia, kad norint ją atrakinti ir perskaityti reikia įdiegti nemokamą programinę įrangą. Norint skaityti šią el. knygą, turite susikurti Adobe ID . Daugiau informacijos  čia. El. knygą galima atsisiųsti į 6 įrenginius (vienas vartotojas su tuo pačiu Adobe ID).

    Reikalinga programinė įranga
    Norint skaityti šią el. knygą mobiliajame įrenginyje (telefone ar planšetiniame kompiuteryje), turite įdiegti šią nemokamą programėlę: PocketBook Reader (iOS / Android)

    Norint skaityti šią el. knygą asmeniniame arba „Mac“ kompiuteryje, Jums reikalinga  Adobe Digital Editions “ (tai nemokama programa, specialiai sukurta el. knygoms. Tai nėra tas pats, kas „Adobe Reader“, kurią tikriausiai jau turite savo kompiuteryje.)

    Negalite skaityti šios el. knygos naudodami „Amazon Kindle“.

Reasoning About Knowledge provides a general discussion of approaches to reasoning about knowledge and its applications to distributed systems, artificial intelligence, and game theory.

Reasoning about knowledge—particularly the knowledge of agents who reason about the world and each other's knowledge—was once the exclusive province of philosophers and puzzle solvers. More recently, this type of reasoning has been shown to play a key role in a surprising number of contexts, from understanding conversations to the analysis of distributed computer algorithms.

Reasoning About Knowledge is the first book to provide a general discussion of approaches to reasoning about knowledge and its applications to distributed systems, artificial intelligence, and game theory. It brings eight years of work by the authors into a cohesive framework for understanding and analyzing reasoning about knowledge that is intuitive, mathematically well founded, useful in practice, and widely applicable. The book is almost completely self-contained and should be accessible to readers in a variety of disciplines, including computer science, artificial intelligence, linguistics, philosophy, cognitive science, and game theory. Each chapter includes exercises and bibliographic notes.
Preface xi
Introduction and Overview
1(14)
The Muddy Children Puzzle
3(4)
An Overview of the Book
7(8)
A Model for Knowledge
15(32)
The Possible-Worlds Model
15(8)
Common Knowledge and Distributed Knowledge
23(1)
The Muddy Children Revisited
24(6)
The Properties of Knowledge
30(6)
An Event-Based Approach
36(11)
Completeness and Complexity
47(56)
Completeness Results
48(14)
Decidability
62(4)
Incorporating Common Knowledge
66(3)
Incorporating Distributed Knowledge
69(2)
The Complexity of the Validity Problem
71(3)
NP-Completeness Results for S5 and KD45
74(2)
The First-Order Logic of Knowledge
76(27)
First-Order Logic
77(3)
First-Order Modal Logic
80(1)
Assumptions on Domains
81(2)
Properties of Knowledge in Relational Kripke Structures
83(20)
Knowledge in Multi-Agent Systems
103(50)
Runs and Systems
103(7)
Incorporating Knowledge
110(4)
Incorporating Time
114(2)
Examples of Systems
116(20)
Knowledge Bases
116(7)
Game Trees
123(4)
Synchronous Systems
127(1)
Perfect Recall
128(3)
Message-Passing Systems
131(2)
Asynchronous Message-Passing Systems
133(3)
Knowledge Gain in A.M.P. Systems
136(17)
Protocols and Programs
153(22)
Actions
153(4)
Protocols and Contexts
157(11)
Programs
168(2)
Specifications
170(5)
Common Knowledge and Agreement
175(58)
Coordinated Attack
176(8)
Agreeing to Disagree
184(6)
Simultaneous Byzantine Agreement
190(7)
Nonrigid Sets and Common Knowledge
197(4)
Attaining SBA
201(6)
Attaining Common Knowledge
207(7)
Clean Rounds
207(2)
Waste
209(3)
Computing Common Knowledge
212(2)
Detailed Proofs
214(19)
Knowledge-Based Programming
233(48)
Knowledge-Based Programs
233(6)
Getting Unique Representations
239(12)
Knowledge Bases Revisited
251(4)
A Knowledge-Based Program for SBA
255(4)
Strong Correctness
259(3)
The Sequence-Transmission Problem
262(7)
Proving Strong Correctness of ST
269(12)
Evolving Knowledge
281(28)
Properties of Knowledge and Time
281(4)
Synchrony and Perfect Recall
285(4)
Knowledge and Time in A.M.P. Systems
289(1)
Knowledge and Time in Inoa (&PHgr;)
290(5)
A Closer Look at Axiom OAn, &PHgr;
295(14)
Logical Omniscience
309(54)
Logical Omniscience
310(3)
Explicit Representation of Knowledge
313(8)
The Syntactic Approach
314(2)
The Semantic Approach
316(4)
Discussion
320(1)
Nonstandard Logic
321(11)
Nonstandard Structures
321(4)
Strong Implication
325(4)
A Payoff: Querying Knowledge Bases
329(2)
Discussion
331(1)
Impossible Worlds
332(5)
Awareness
337(5)
Local Reasoning
342(5)
Concluding Remarks
347(16)
Knowledge and Computation
363(22)
Knowledge and Action Revisited
363(3)
Algorithmic Knowledge
366(5)
Algorithmic Systems
366(4)
Properties of Algorithmic Knowledge
370(1)
Examples
371(3)
Algorithmic Programs
374(11)
Algorithmic Programming
374(2)
Algorithmic Knowledge and Complexity
376(2)
Implementing Knowledge-Based Programs
378(7)
Common Knowledge Revisited
385(44)
Common Knowledge as a Conjunction
386(2)
Common Knowledge and Simultaneity
388(7)
Common Knowledge and Uncertainty
388(3)
Simultaneous Events
391(4)
Temporal Imprecision
395(2)
The Granularity of Time
397(5)
Common Knowledge as a Fixed Point
402(9)
Fixed Points
402(7)
Downward Continuity and Infinite Conjunctions
409(2)
Approximations of Common Knowledge
411(10)
E- and Eventual Common Knowledge
412(3)
Applications to Coordinated Attack
415(3)
Timestamped Common Knowledge
418(3)
Other Approximations of Common Knowledge
421(1)
Discussion
421(8)
Bibliography 429(20)
Index 449(26)
Symbol Index 475