Understanding Planning Tasks : Domain Complexity and Heuristic Decomposition - Malte Helmert

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Understanding Planning Tasks

Domain Complexity and Heuristic Decomposition

By: Malte Helmert

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Paperback | 24 January 2008

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288 Pages

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Action planning has always played a central role in Artificial Intelligence. Given a description of the current situation, a description of possible actions and a description of the goals to be achieved, the task is to identify a sequence of actions, i.e., a plan that transforms the current situation into one that satisfies the goal description.

This monograph is a revised version of Malte Helmert's doctoral thesis, Solving Planning Tasks in Theory and Practice, written under the supervision of Professor Bernhard Nebel as thesis advisor at Albert-Ludwigs-Universitaet Freiburg, Germany, in 2006. The book contains an exhaustive analysis of the computational complexity of the benchmark problems that have been used in the past decade, namely the standard benchmark domains of the International Planning Competitions (IPC). At the same time, it contributes to the practice of solving planning tasks by presenting a powerful new approach to heuristic planning. The author also provides an in-depth analysis of so-called routing and transportation problems.

All in all, this book will contribute significantly to advancing the state of the art in automatic planning.

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Non-Fiction Reference, Information & Interdisciplinary Subjects Encyclopaedias & Reference Works Computing & I.T.Computer Science Artificial Intelligence Computer Programming & Software Development Algorithms & Data Structures

Planning Benchmarks
The Role of Benchmarks	p. 3
Evaluating Planner Performance	p. 3
Worst-Case Evaluation	p. 4
Average-Case Evaluation	p. 5
Planning Benchmarks Are Important	p. 7
Theoretical Analyses of Planning Benchmarks	p. 8
Why Theoretical Analyses Are Useful	p. 8
Published Results on Benchmark Complexity	p. 9
Standard Benchmarks	p. 9
Summary and Overview	p. 11
Defining Planning Domains	p. 13
Optimization Problems	p. 13
Minimization Problems	p. 14
Approximation Algorithms	p. 15
Approximation Classes	p. 16
Reductions	p. 18
Formalizing Planning Domains	p. 21
General Results and Reductions	p. 24
Upper Bounds	p. 24
Shortest Plan Length	p. 25
Approximation Classes of Limited Interest	p. 26
Relating Planning and (Bounded) Plan Existence	p. 28
Generalization and Specialization	p. 29
The Benchmark Suite	p. 31
Defining the Competition Domains	p. 31
The Benchmark Suite	p. 32
IPC1 Domains	p. 32
IPC2 Domains	p. 34
IPC3 Domains	p. 34
IPC4 Domains	p. 35
Domains and Domain Families	p. 36
Transportation and Route Planning	p. 39
Transport and Route	p. 39
The Transport Domain	p. 41
The Route Domain	p. 43
Special Cases and Hierarchy	p. 44
General Results	p. 46
Plan Existence	p. 52
Hardness of Optimization	p. 54
Constant Factor Approximation	p. 59
Hardness of Constant Factor Approximation	p. 62
Summary	p. 68
Beyond Transport and Route	p. 71
IPC Domains: Transportation and Route Planning	p. 75
Gripper	p. 75
Mystery and Mystery Prime	p. 76
Logistics	p. 78
Zenotravel	p. 83
Depots	p. 85
Miconic-10	p. 88
Rovers	p. 93
Grid	p. 98
Driverlog	p. 103
Airport	p. 108
Summary	p. 111
IPC Domains: Others	p. 113
Assembly	p. 113
Blocksworld	p. 117
Freecell	p. 117
Movie	p. 126
Pipesworld	p. 127
Promela	p. 132
PSR	p. 138
Satellite	p. 142
Schedule	p. 145
Summary	p. 149
Conclusions	p. 151
Ten Conclusions	p. 151
Going Further	p. 154
Fast Downward
Solving Planning Tasks Hierarchically	p. 157
Introduction	p. 157
Related Work	p. 163
Causal Graphs and Abstraction	p. 164
Causal Graphs and Unary STRIPS Operators	p. 165
Multi-Valued Planning Tasks	p. 167
Architecture and Overview	p. 168
Translation	p. 171
PDDL and Multi-valued Planning Tasks	p. 171
Translation Overview	p. 175
Normalization	p. 176
Compiling Away Types	p. 177
Simplifying Conditions	p. 177
Simplifying Effects	p. 179
Normalization Result	p. 179
Invariant Synthesis	p. 180
Initial Candidates	p. 182
Proving Invariance	p. 183
Refining Failed Candidates	p. 186
Examples	p. 188
Related Work	p. 188
Grounding	p. 190
Overview of Horn Exploration	p. 191
Generating the Logic Program	p. 191
Translating the Logic Program to Normal Form	p. 193
Computing the Canonical Model	p. 195
Axiom and Operator Instantiation	p. 197
Multi-valued Planning Task Generation	p. 197
Variable Selection	p. 198
Converting the Initial State	p. 199
Converting Operator Effects	p. 200
Converting Conditions	p. 201
Computing Axiom Layers	p. 202
Generating the Output	p. 202
Performance Notes	p. 203
Relative Performance Compared to MIPS Translator	p. 203
Absolute Performance	p. 205
Knowledge Compilation	p. 207
Overview	p. 207
Domain Transition Graphs	p. 208
Causal Graphs	p. 213
Acyclic Causal Graphs	p. 214
Generating and Pruning Causal Graphs	p. 215
Causal Graph Examples	p. 217
Successor Generators and Axiom Evaluators	p. 220
Successor Generators	p. 220
Axiom Evaluators	p. 221
Search	p. 223
Overview	p. 223
The Causal Graph Heuristic	p. 224
Conceptual View of the Causal Graph Heurstic	p. 225
Computation of the Causal Graph Heuristic	p. 226
States with Infinite Heuristic Value	p. 228
Helpful Transitions	p. 229
The FF Heuristic	p. 230
Greedy Best-First Search in Fast Downward	p. 231
Preferred Operators	p. 231
Deferred Heuristic Evaluation	p. 232
Multi-heuristic Best-First Search	p. 233
Focused Iterative-Broadening Search	p. 234
Experiments	p. 239
Experiment Design	p. 239
Benchmark Set	p. 240
Experiment Setup	p. 242
Translation and Knowledge Compilation vs. Search	p. 243
Strips Domains from IPC1-3	p. 243
ADL Domains from IPC1-3	p. 246
Domains from IPC4	p. 248
Conclusions from the Experiment	p. 251
Discussion	p. 253
Summary	p. 253
Major Contributors	p. 254
Multi-valued Representations	p. 254
Task Decomposition Heuristics	p. 256
Minor Contributions	p. 257
Going Further	p. 258
References	p. 259
Index	p. 267
Table of Contents provided by Ingram. All Rights Reserved.

Understanding Planning Tasks

Domain Complexity and Heuristic Decomposition

At a Glance

Paperback

Shipping

How to return your order

Defective items

You Can Find This Book In

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