AI 2010: Advances in Artificial Intelligence: 23rd Australasian Joint Conference, Adelaide, Australia, December 7-10, 2010. Proceedings

Cover......Page 1
Lecture Notes in Artificial Intelligence 6464......Page 2
AI 2010: Advances in
Artificial Intelligence......Page 3
ISBN-13 9783642174315......Page 4
Preface......Page 6
Conference Organization......Page 8
Table of Contents......Page 14
Introduction......Page 20
Game Description Language......Page 21
Formalising and Encoding Temporal Game Properties......Page 23
Proving Multiple Temporal Game Properties at Once......Page 24
Expressiveness and Correctness of the Proof Method......Page 26
Experimental Results......Page 27
References......Page 29
Introduction......Page 30
Temporal Ranking Function: Temporal Belief Framework......Page 32
Temporal $κ$ and AGM Revision......Page 35
Temporal $κ$ and KM Belief Update......Page 36
Discussion and Conclusion......Page 38
References......Page 39
Introduction......Page 41
Sequence-Indexed Linear Logic......Page 43
Main Theorems......Page 45
Applications......Page 47
References......Page 50
Introduction......Page 51
Journaling System......Page 52
Causality Tracking Mechanism......Page 54
Example......Page 57
Conclusion......Page 59
References......Page 60
Introduction......Page 61
Preliminaries......Page 62
Belief Revision Issue......Page 63
Preference Ordering over Terms......Page 64
Prime Implicant Based Revision......Page 66
Relevant Revision......Page 67
Conclusion......Page 68
References......Page 69
Introduction......Page 71
Background......Page 72
Partial Imaging......Page 74
Probabilistic Removal Functions......Page 75
Variants of Imaging......Page 76
Selective Imaging......Page 77
Selective Partial Imaging......Page 78
Discussion and Conclusion......Page 79
References......Page 80
Introduction......Page 81
A General Definition of QSTR Applications......Page 83
Selecting QSTR Calculi......Page 84
Qualification When Input Is a Consistent Atomic Network......Page 85
Qualification When Input Is a Consistent Non-Atomic Network......Page 86
Qualification When Input Is an Inconsistent Network......Page 87
Properties of QSTR Applications......Page 88
Conclusions......Page 89
References......Page 90
Introduction and Background......Page 91
Contractions under Horn Logic......Page 93
Transitively Relational Partial Meet Horn Contraction......Page 95
Connections between EEHC and TRPMHC......Page 97
References......Page 100
Introduction......Page 101
Minimum Message Length......Page 102
A Typical Normalization Procedure - An Example......Page 103
MML Interpretation of Normalization......Page 105
Conclusion and Future Work......Page 109
References......Page 110
Introduction......Page 111
Related Work......Page 112
Reduce UK-means to K-means......Page 113
Approximate UK-means......Page 114
Experimental Evaluation......Page 115
Execution Time......Page 116
Clustering Results......Page 118
References......Page 120
Introduction......Page 121
Term-Category Weighting......Page 122
Maximum Gap......Page 124
Experiments......Page 126
Experimental Results......Page 128
References......Page 129
Introduction......Page 131
Traditional Clustering Methods......Page 132
Practical Stochastic Clustering Method......Page 133
Experiments and Results......Page 135
References......Page 139
Introduction......Page 141
Patterns and Outliers in Mixed Attribute Data......Page 143
Experimental Results and Comparison......Page 146
Synthetic Data......Page 147
Real World Data......Page 148
References......Page 150
Introduction......Page 151
The SVD in Data Mining......Page 152
Projection Vector Machine......Page 153
The Proposed Algorithm: Incremental Projection Vector Machine......Page 154
Selections of Parameters......Page 156
Experimental Results and Analysis......Page 157
Conclusions and Future Work......Page 159
References......Page 160
Introduction......Page 161
Related Work......Page 162
Contributions......Page 163
Human Pose Estimation......Page 164
Human Activity Recognition......Page 166
Experiments......Page 168
References......Page 170
Introduction......Page 172
An Overview : LLR and PRS......Page 174
Schema for the Proposed Solution......Page 176
Experimental Set-Up, Results and Evaluation......Page 177
Conclusions......Page 180
References......Page 181
Introduction......Page 183
Preliminaries......Page 185
Two Stage Voting Architecture (TSVA)......Page 187
Experimental Results......Page 188
Conclusion......Page 191
References......Page 192
Introduction......Page 193
Notation......Page 194
Related Work......Page 195
Gravitational Partitions......Page 196
Tree Generation......Page 197
Stochastic Probability Calculation......Page 198
Experiments......Page 200
Conclusions and Future Work......Page 201
References......Page 202
Introduction......Page 203
Semantic Features......Page 204
Event-Based Features......Page 205
Other Features......Page 206
Experiments......Page 207
Classification Model Reverse Engineering......Page 209
Concluding Remarks......Page 210
References......Page 211
Introduction......Page 213
Related Work......Page 215
Approach......Page 216
Experimental Results......Page 218
Conclusion......Page 221
References......Page 222
Introduction......Page 223
$t$-Distributed SNE......Page 225
Laplacian-distrubted (L1) SNE......Page 226
Handwritten Digits......Page 227
Conclusions......Page 230
References......Page 231
Introduction......Page 232
Stepwise Regression......Page 233
Penalized Logistic Regression......Page 234
Elastic Net......Page 235
Empirical Comparison......Page 236
A Simulation Study......Page 237
Real Data Examples......Page 238
References......Page 241
Introduction......Page 242
Models and Nested Model Sequences......Page 243
Model Fitting and Goodness of Fit......Page 244
Akaike's Information Criterion......Page 245
The Bias in AIC for Multiple Selection......Page 246
Discussion and Impact......Page 248
Forward Selection of Regression Features......Page 249
Application: Signal Denoising by Wavelet Thresholding......Page 250
References......Page 251
Introduction......Page 252
The Knowledge Base......Page 253
The Entity-Attribute Truth Table......Page 254
Acquisition......Page 256
A Question-Question Correspondence Matrix......Page 257
Question Selection and Knowledge Acquisition......Page 258
The Procedure......Page 259
Remarks......Page 260
References......Page 261
Introduction......Page 262
GP Framework and Classification Strategies......Page 263
GP Fitness Functions......Page 265
Experimental Parameters, Setup and Data Sets......Page 267
Experimental Results and Analysis......Page 268
Conclusions......Page 270
References......Page 271
Introduction......Page 272
Preliminaries......Page 273
The New Encoding Scheme: Neuron Based Subpopulation (NSP)......Page 274
Number of Generations in Subpopulation......Page 277
Analysis and Discussion......Page 278
Conclusions and Future Work......Page 280
References......Page 281
Introduction......Page 282
The Model......Page 284
Strategy Representation......Page 285
Experiments and Results......Page 286
References......Page 290
Introduction......Page 292
Background......Page 293
New Sampling Methods......Page 294
Experimental Design......Page 295
Experimental Results......Page 296
Conclusions......Page 300
References......Page 301
Introduction......Page 302
Evolutionary Art......Page 303
Configuration of Genetic Programming......Page 304
Open and Closed Triangular Strokes......Page 305
Open vs. Closed Triangular Brushstrokes......Page 306
Different Size of Triangles......Page 307
Different Stroke Placement Modes......Page 309
Conclusion......Page 310
References......Page 311
Introduction......Page 312
Cellular Genetic Algorithm (cGA)......Page 313
Differential Evolution (DE)......Page 314
Cellular Differential Evolution (cDE)......Page 315
Experimental Setup......Page 316
Results and Analysis......Page 317
References......Page 320
Introduction......Page 322
Cooperative Co-evolution......Page 324
Covariance Matrix Adaptation Evolution Strategy......Page 325
Experimental Results and Analysis......Page 328
References......Page 330
Introduction......Page 332
Particle Swarm Optimisation......Page 333
New Hybrid PSO Algorithms......Page 334
Discussion......Page 335
Multi-modal and High-Dimensional Functions......Page 336
Experimental Results and Discussion......Page 338
Conclusions......Page 340
References......Page 341
Introduction......Page 342
Particle Swarm Optimisation......Page 343
PSO for Low Level Feature Extraction......Page 344
PSO-Based Algorithm for Edge Detection......Page 345
New PSO-Based Algorithm for Corner Detection......Page 346
Experimental Design......Page 347
Results and Discussion......Page 349
Conclusions......Page 350
References......Page 351
Introduction......Page 353
Proposed Algorithms......Page 355
Fuzzy Uniform Fish (FUF)......Page 356
Fuzzy Autonomous Fish (FAF)......Page 357
Experimental Results......Page 359
References......Page 362
Introduction......Page 363
Information-Based Agency That Handles Relationships......Page 364
An Architecture to Enable Relationships......Page 365
Valuing Dialogues......Page 366
Relationship Strategies and Tactics......Page 367
Providing Agents with Information from External Sources......Page 369
Conclusions......Page 371
References......Page 372
Introduction and Related Work......Page 373
Test Description......Page 375
Java Tuning......Page 376
Performance Evaluation......Page 379
Conclusions and Future Work......Page 381
References......Page 382
Altruism of Army Ants......Page 383
Defining the Problem......Page 384
Hypotheses......Page 385
Experiment to Verify the Hypotheses......Page 386
What Is Chain Formation?......Page 387
Experiment to Verify the Chain Formation System......Page 388
Comparative Experiment......Page 389
Simulation with Fixed Role Assigned......Page 391
Conclusion......Page 392
References......Page 393
Introduction......Page 394
CP-Net Overview......Page 395
The Topological Order of Variables......Page 397
Making Social Choices with RA-Trees......Page 398
References......Page 403
Introduction......Page 404
Related Work......Page 405
Formal Description......Page 407
The Coordination Process......Page 408
Empirical Evaluation......Page 410
Conclusions and Future Work......Page 412
References......Page 413
Introduction and Motivation......Page 414
A Logic for Actions and Observations......Page 415
Semantics......Page 416
Specifying Domains in LAO......Page 418
Tableaux for LAO......Page 420
Discussion and Related Work......Page 421
Concluding Remarks......Page 422
References......Page 423
Introduction......Page 424
Problem Formulation......Page 425
Related Work......Page 426
Offline Stage......Page 427
Online Stage......Page 429
Theoretical Analysis......Page 430
Database Generation......Page 431
Online Performance......Page 432
References......Page 433
Introduction......Page 434
The Variable Selection Scheme......Page 435
Computation of Several Actions......Page 438
Evaluation......Page 439
References......Page 442
Introduction......Page 444
Infeasibility Driven Evolutionary Algorithm (IDEA)......Page 446
Infeasibility Empowered Memetic Algorithm (IEMA)......Page 448
Experimental Setup......Page 449
Results......Page 450
Summary and Future Work......Page 451
References......Page 452
Introduction......Page 454
Word Sense Disambiguation and Synonym Expansion......Page 455
The Role of Word Sense Disambiguation (WSD)......Page 456
Increasing Semantic Context through Synonym Expansion......Page 457
Word Sense Disambiguation......Page 458
Word-to-Word Semantic Similarity......Page 459
Textual Entailment Recognition......Page 460
30-Sentences Dataset......Page 461
Conclusion......Page 462
References......Page 463
Introduction......Page 464
Related and Prior Work......Page 465
Creating our Corpus of Legal Citations......Page 466
Building Legal Citation Classification Systems......Page 468
Experimental Results......Page 469
Conclusions and Future Work......Page 471
References......Page 472
Introduction......Page 474
Proposed Algorithms......Page 475
Generation of Keyword Set......Page 476
Generation of Segment Pairs......Page 477
Expansion with a Thesaurus......Page 479
Experimental Environments......Page 480
Experimental Results......Page 481
References......Page 483
Introduction......Page 485
Sentence Similarity Measures......Page 486
Word-to-Word Semantic Similarity Measures......Page 487
Graph-Based Word Importance Ranking......Page 488
Modified Sentence Similarity Measures......Page 489
Spectral Clustering......Page 490
Clustering Evaluation Criteria......Page 491
Results......Page 492
Conclusion......Page 493
References......Page 494
Introduction......Page 495
People to People Recommendation......Page 496
A Prototypical Collaborative Filtering Algorithm......Page 497
Collaborative Filtering for Social Networks......Page 498
Evaluation Metrics......Page 501
Results of Recommendation......Page 502
Concluding Remarks......Page 503
References......Page 504
Introduction......Page 505
Face Synthesis......Page 506
Speech Animation......Page 508
External Interfaces......Page 510
Applications......Page 512
References......Page 513
Introduction......Page 515
Motivating Example......Page 516
Diagnosis Model......Page 517
Diagnosis Computation......Page 520
Evaluation......Page 522
Conclusion......Page 523
References......Page 524
Introduction......Page 525
Multi-robot Co-ordination......Page 526
Dynamic Task Allocation......Page 528
Experimental Setting......Page 529
Experimental Results and Evaluation......Page 531
Conclusions and Further Work......Page 533
References......Page 534
Introduction......Page 535
The Market Model......Page 536
Maximal Matching......Page 537
Maximizing the Number of Transactions......Page 540
Maximizing Profit......Page 541
Experimental Results......Page 542
References......Page 544
Author Index......Page 546