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Knowledge in action : logical foundations for specifying and implementing dynamical systems
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Knowledge in action : logical foundations for specifying and implementing dynamical systems

Author: Raymond Reiter
Publisher: Cambridge, Mass. : MIT Press, ©2001.
Edition/Format:   Book : eBook : EnglishView all editions and formats
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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Raymond Reiter
ISBN: 0262182181 9780262182188
OCLC Number: 46456413
Description: xvi, 424 p. : ill. ; 24 cm.
Contents: 2 Logical Preliminaries 5 --
2.1 First-Order Logic 5 --
2.1.1 Syntax 5 --
2.1.2 Semantics 6 --
2.1.3 Soundness and Completeness 8 --
2.1.4 Many-Sorted First-Order Languages 8 --
2.1.5 Reducing Many-Sorted Logic to Standard Logic 10 --
2.1.6 Some Useful First-Order Inference Rules 10 --
2.1.7 A Limitation of First-Order Logic 10 --
2.2 Second-Order Logic 12 --
2.2.1 Syntax 12 --
2.2.2 Semantics 12 --
2.2.3 Inductive Definitions and Second-Order Logic 13 --
2.2.4 Incompleteness of Second-Order Logic 15 --
3 Introduction to the Situation Calculus 19 --
3.1 Situation Calculus 19 --
3.1.1 Intuitive Ontology for the Situation Calculus 19 --
3.1.2 Axiomatizing Actions in the Situation Calculus 20 --
3.1.3 Qualification Problem for Actions 20 --
3.1.4 Frame Problem 22 --
3.2 A Simple Solution to the Frame Problem (Sometimes) 23 --
3.2.1 Frame Axioms: Pednault's Proposal 24 --
3.2.2 Frame Axioms: The Davis/Haas/Schubert Proposal 26 --
3.2.3 A Simple Solution (Sometimes) 28 --
3.2.4 Aside: Normal Forms for Effect Axioms 29 --
3.2.5 A Simple Solution: The General Case 30 --
3.2.6 A Simple Solution: Functional Fluents 32 --
3.2.7 A Simple Solution: Summary 34 --
3.2.8 Some Limitations of These Action Descriptions 35 --
3.3 Deductive Planning with the Situation Calculus 35 --
3.4 Formalizing Database Transactions in the Situation Calculus 39 --
3.4.1 Motivation and Background 39 --
3.4.2 Database Updates: A Proposal 39 --
3.4.3 Basic Approach: An Example 39 --
3.4.4 Querying a Situation Calculus Database 41 --
4 Foundations of the Situation Calculus 47 --
4.1 Language of the Situation Calculus 47 --
4.2 Axioms for the Situation Calculus 48 --
4.2.1 Number Theory 48 --
4.2.2 Foundational Axioms for Situations 49 --
4.2.3 Some Consequences of the Foundational Axioms 52 --
4.2.4 Executable Situations 52 --
4.2.5 Further Consequences of the Foundational Axioms 53 --
4.3 Reasoning about Situations Using Induction 54 --
4.3.1 Some Examples of Inductive Proofs 55 --
4.3.2 State Constraints 57 --
4.4 Basic Theories of Action 58 --
4.5 Regression 61 --
4.6 Using Regression 67 --
4.6.1 Executable Ground Action Sequences 67 --
4.6.2 Projection Problem and Query Evaluation 69 --
4.7 Regression with Functional Fluents 70 --
4.8 Database Logs and Historical Queries 73 --
4.8.1 Querying All Past Situations 74 --
4.8.2 Querying Some Past Situation 76 --
4.8.3 Projection Problem Revisited 77 --
5 Implementing Basic Action Theories 85 --
5.1 Logical Foundations of Prolog 85 --
5.1.1 Why Insist on a Proper Prolog Interpreter? 87 --
5.1.2 More on the Equational Theory of Clark's Theorem 88 --
5.2 Lloyd-Topor Normal Forms for Arbitrary Definitions and Goals 90 --
5.2.1 What Are the Lloyd-Topor Auxiliary Predicates? 91 --
5.2.2 Accommodating Arbitrary Goals 92 --
5.2.3 Definitional Theories: Soundness, Completeness, and Closed Worlds 94 --
5.3 Basic Action Theories, Definitions, and Regressable Queries 95 --
5.3.1 Definitional Form for Action Precondition Axioms 96 --
5.3.2 Definitional Form for Successor State Axioms 96 --
5.3.3 Unfolding the Lloyd-Topor Auxiliary Predicates 102 --
5.3.4 Revised Lloyd-Topor Transformations 102 --
6 Complex Actions, Procedures, and Golog 111 --
6.1 Complex Actions and Procedures in the Situation Calculus 111 --
6.1.1 Procedures 114 --
6.1.2 Programs and Executable Situations 116 --
6.1.3 Why Macros? 117 --
6.1.4 Programs as Macros: What Price Must Be Paid? 118 --
6.1.5 Golog 119 --
6.2 An Elevator Controller in Golog 119 --
6.3 Implementation 122 --
6.3.1 An Interpreter 122 --
6.3.2 Assumptions Underlying the Implementation 125 --
6.3.3 Correctness of the Interpreter for Basic Action Theories with Closed Initial Database 126 --
6.3.4 Elevator Example 129 --
6.3.5 University ofu Toronto Implementation of Golog 132 --
6.5 Proving Properties of Golog Programs 134 --
6.5.1 Induction Principle for While Loops 135 --
6.5.2 Example: A Blocks World 136 --
7 Time, Concurrency, and Processes 149 --
7.1 Concurrency and Instantaneous Actions 149 --
7.2 Concurrency via Interleaving 150 --
7.2.1 Examples of Interleaved Concurrency 151 --
7.2.2 Limitations of Interleaved Concurrency 152 --
7.3 Sequential, Temporal Situation Calculus 152 --
7.3.1 Concurrent Temporal Processes 154 --
7.4 Sequential, Temporal Golog 155 --
7.4.1 Example: A Coffee Delivery Robot 156 --
7.4.2 A Singing Robot 162 --
7.4.3 Plan-Execution Monitoring 163 --
7.5 Concurrent, Non-Temporal Situation Calculus 164 --
7.6 Axiomatizing Concurrent Worlds 166 --
7.6.1 Successor State Axioms 166 --
7.6.2 Action Precondition Axioms 166 --
7.7 Concurrent, Temporal Situation Calculus 167 --
7.8 Concurrent, Temporal Golog 169 --
7.9 Natural Actions 170 --
7.9.1 Representing Physical Laws 170 --
7.9.2 Permissiveness of the Situation Calculus 171 --
7.9.3 Natural Actions and Executable Situations 172 --
7.9.4 An Example: Enabling Actions 173 --
7.9.5 Zeno's Paradox 173 --
7.9.6 Natural-World Assumption 174 --
7.9.7 Least-Natural-Time Points 174 --
7.9.8 Simulating Natural Worlds 176 --
7.9.9 Animating Natural Worlds 180 --
8 Exogenous Actions, Interrupts, and Reactive Golog 185 --
8.1 Interrupts 185 --
8.2 Semantics of RGolog 187 --
8.2.1 Intuitive Semantics of RGolog 187 --
8.2.2 Formal Semantics of RGolog 188 --
8.3 An RGolog Interpreter 190 --
8.4 Example: A Reactive Elevator Controller 191 --
8.4.1 A Reactive Elevator with Interactively Generated Exogenous Actions 193 --
8.4.2 A Reactive Elevator with Randomly Generated Exogenous Actions 197 --
8.5 Interrupts with Priorities 198 --
8.6.1 Sensing and Exogenous Actions 200 --
8.6.2 On-Line vs. Off-Line Program Execution 200 --
9 Progression 205 --
9.1 Logical Foundations of Progression 207 --
9.1.1 Finite Progression Is Second-Order Definable 209 --
9.1.2 Progression Is Not Always First-Order Definable 210 --
9.1.3 But Why Not Do the Obvious? 210 --
9.2 Two First-Order Progressable Cases 210 --
9.2.1 Progressing Relatively Complete Databases 210 --
9.2.2 Context-Free Successor State Axioms and the Progression of Isolated Fluents 213 --
9.3 STRIPS Planning Systems 216 --
9.3.1 STRIPS Databases 216 --
9.3.2 STRIPS Operator Descriptions 218 --
9.3.3 Planning with STRIPS 221 --
9.4 Strongly Context-Free Successor State Axioms 223 --
9.5 Progression and Relational STRIPS 224 --
9.6 An Open-World STRIPS 226 --
9.7 Correctness of Relational and Open-World STRIPS 228 --
10 Planning 233 --
10.1 A Simple Breadth-First Planner 233 --
10.2 Example: Planning in the Blocks World 235 --
10.2.1 A Planning Problem Example 239 --
10.3 Planning with Concurrent Actions 242 --
10.4 OCTOPUS: A Multi-Handed Blocks World Agent 247 --
10.5 A Simple Depth-First Planner 255 --
10.6 Open-World Planning 259 --
10.6.1 Prime Implicates and Compiling an Initial Database 259 --
10.6.2 A Regression-Based Theorem-Prover 266 --
10.6.3 Bad Situations for Open-World Planning 268 --
10.6.4 Axiomatizing Incomplete Initial Situations 268 --
10.6.5 A Blocks World with Incomplete Initial Situation 270 --
10.7 Planning vs. Nondeterministic Programming 275 --
11 Sensing and Knowledge 283 --
11.1 Knowledge in the Situation Calculus 283 --
11.1.1 Accessibility Relations and Knowledge 284 --
11.1.2 Alternatives to the Initial Situation 286 --
11.1.3 Knowing a Referent 287 --
11.1.4 Knowledge and Action 287 --
11.1.5 Knowledge Defined 288 --
11.1.6 Some Consequences of This Approach 289 --
11.1.7 A Useful Notation 290 --
11.1.8 Quantifiers and Knowledge 291 --
11.2 Knowledge and the Designer's Perspective 292 --
11.2.1 Logical Omniscience Revisited 293 --
11.3 Knowledge-Producing Actions 293 --
11.4 Frame Problem for Knowledge-Producing Actions 294 --
11.4.1 No-Side-Effects Assumption for Knowledge-Producing Actions 294 --
11.4.2 A Successor State Axiom for K 295 --
11.4.3 More General Knowledge-Producing Actions 299 --
11.4.4 Some Consequences of this Solution 299 --
11.5 Accessibility in the Initial Situation 302 --
11.5.1 New Foundational Axioms for Situations 302 --
11.5.2 Some Possible Accessibility Relations 304 --
11.5.3 Basic Action Theories for Knowledge 305 --
11.6 Regression for Knowledge-Producing Actions 306 --
11.7 Knowledge-Based Programming 309 --
11.7.1 Two Simplifying Assumptions 312 --
11.7.2 Sense Actions 312 --
11.7.3 Reducing Knowledge to Provability for the Initial Situation 313 --
11.7.4 On-Line Execution of Knowledge-Based Programs 314 --
11.7.5 Reduction of Knowledge to Provability for On-Line Programs 315 --
11.7.6 Dynamic Closed-World Assumption 318 --
11.7.7 Interpreter for Knowledge-Based Programs with Sensing 321 --
11.7.8 Computing Closed-World Knowledge 322 --
11.7.9 Putting It All Together 322 --
12 Probability and Decision Theory 335 --
12.1 Stochastic Actions and Probability 335 --
12.1.1 How to Specify a Probabilistic Domain: A Guide for the Perplexed 339 --
12.1.2 Some Properties of the Specification 341 --
12.2 Derived Probabilities 341 --
12.2.1 stGolog: Stochastic Golog 345 --
12.3 Exogenous Events 349 --
12.4 Uncertainty in the Initial Situation 359 --
12.5 Markov Decision Processes 363 --
12.5.1 Sensing and stGolog Programs 366 --
12.5.2 Fully Observable MDPs 369 --
12.5.3 Partially Observable MDPs 372 --
12.5.4 Implementing Policies: Run-Time Sense Actions 376 --
12.5.5 Exogenous Actions 378 --
12.5.6 Solving MDP Planning Problems 378
Responsibility: Raymond Reiter.

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