Advances in Artificial Intelligence: 18th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2005, Victoria,

Front matter......Page 1
Introduction......Page 13
Recursive Bayes Filter......Page 14
Dynamic Maps......Page 15
Binary Object Bayes Filtering......Page 16
Cell Correlations......Page 17
Algorithm......Page 19
Results......Page 20
Related Work......Page 22
References......Page 23
Introduction......Page 25
Definition......Page 26
Difficulties with Current Approaches......Page 27
Constraint Density in Distributed Over-Constrained Satisfaction Problems......Page 29
Algorithm......Page 30
Experimental Results......Page 33
Conclusion......Page 35
Introduction......Page 37
System Architecture and Distributed Learning Algorithm......Page 38
Performance Evaluation of Distributed Mining Process......Page 40
Experimentation......Page 41
Conclusion and Future Work......Page 42
References......Page 43
Coordinator-Based Adjustable Autonomy......Page 45
Coordinating Reasoning About Decision Transfers......Page 46
Discussion......Page 49
Introduction......Page 50
The Environment......Page 51
World Rules, Environment Features, and Their Connection to Multi-agent Systems......Page 52
Experimental Evaluation......Page 53
References......Page 54
Modelling of the Tasks Scheduling System......Page 55
Third Step: Scheduling Algorithm Definition......Page 56
Step 2: Scheduler Type Definition......Page 57
Results......Page 58
Conclusion......Page 59
Introduction......Page 60
Robot Platform......Page 61
Reactive Planning Process......Page 62
Conference Planner......Page 63
References......Page 64
Introduction......Page 65
Decision Theoretic Meta-reasoning......Page 66
The Branch-and-Bound Search Method......Page 67
The Meta-reasoning Problem......Page 68
A Statistical Model for Predicting Outcomes of Computation......Page 71
User Preference Models......Page 72
Testing the Meta-reasoning Solver......Page 73
Testing Different User Preference Models......Page 74
Summary and Future Work......Page 75
References......Page 76
Introduction......Page 78
Abstract Combat Games......Page 79
Heuristic Search in Abstract Combat Games......Page 80
Randomized Alpha--Beta Search (RAB)......Page 83
Experiments......Page 85
Conclusion and Future Work......Page 89
Introduction......Page 91
Background......Page 93
The Curriculum Planning System......Page 94
Definitions of the System and Its Constraints......Page 95
Searching Methods......Page 96
Variable and Value Ordering......Page 99
Experimental Results......Page 100
Conclusion......Page 101
Introduction......Page 103
Navigation......Page 104
The SWAMI Architecture......Page 105
The User Representation......Page 106
The Search Components......Page 107
Implementation......Page 108
Example 1: Interest Shifts......Page 109
Example 2: Interest Specialization......Page 111
Discussion and Conclusions......Page 113
Introduction......Page 115
Experimental Results......Page 117
Conclusion......Page 119
Introduction......Page 120
Cursor Prediction......Page 121
Learning Bayesian Networks......Page 122
Restricted Classes of Bayesian Networks......Page 123
A Bayesian Network for Cursor Prediction......Page 124
Results......Page 125
Future Work......Page 129
Conclusion......Page 131
Introduction......Page 132
DBSCAN......Page 133
DBRS......Page 134
Comparison from the Viewpoint of Neighborhood Graphs......Page 136
Comparison from the Viewpoint of Skeletal Points......Page 138
Performance Evaluation......Page 139
Scalability......Page 140
Scalability with Respect to the Number of Noise Points......Page 141
Real Dataset......Page 142
References......Page 143
Introduction......Page 145
Problem Formalization......Page 147
States......Page 148
Rewards......Page 149
The Transition Function......Page 150
The Dynamic Programming Model......Page 151
Testing the Performance......Page 152
Our \NaRC" Agent......Page 154
Conclusions and Future Work......Page 155
References......Page 156
Electronic Negotiations......Page 157
Electronic Business Negotiations......Page 158
Learning Strategies from Corpora......Page 159
Negotiation Strategies and Language......Page 162
Classification of the Negotiation Outcomes-and Discussion......Page 164
Conclusions and Future Work......Page 167
Introduction......Page 170
A Principal Component Null Space Analysis Based Approach......Page 171
The Protein Sequence Dataset......Page 173
Experiments and Results......Page 174
Two-Class Scenario......Page 175
Four-Class Scenario......Page 176
Conclusion and Future Work......Page 179
Introduction......Page 182
Automata and Trajectories......Page 183
Synchronized Automata......Page 184
Objectives......Page 185
Automata Chain......Page 186
Synchronization of Automata Chain......Page 188
Diagnosis Chain......Page 190
Incremental Synchronization......Page 191
Conclusion......Page 192
Introduction......Page 194
Related Work......Page 195
Document Clustering......Page 196
Association Rule Mining......Page 199
Internal Cluster Evaluation......Page 200
Association Rule Mining Evaluation......Page 201
Conclusion and Future Work......Page 202
Introduction......Page 206
The Envisioned Engine......Page 207
Overall Design......Page 208
Detailed Description of the Prototype......Page 210
Experimental Results......Page 214
Conclusions and Future Work......Page 215
Introduction......Page 217
Spatial Clustering......Page 218
Ontologies and the OWL Web Ontology Language......Page 219
Ontology-Based Spatial Clustering......Page 220
Application to Canadian Population Data......Page 223
References......Page 227
Target Movement Prediction......Page 229
Experimentation......Page 231
References......Page 233
Introduction......Page 234
Image Classification......Page 235
Environments......Page 236
Results......Page 237
References......Page 238
Probabilistic Modelling of Person Identity Uncertainty......Page 239
The Model of Attribute Dependence for HypothesisX = Y......Page 240
Inference......Page 241
Experimental Evaluation......Page 242
References......Page 243
Introduction......Page 244
The Logic of Induction and Default Logic......Page 245
Plausibility and Paraconsistency......Page 246
A Logic of Inductive Implication......Page 248
Default Logic, Universal Defaults and Anomalous Extensions......Page 250
A Calculus of Defaults: Cumulativity, And, Or and Rationality......Page 252
Conclusion......Page 254
References......Page 255
Introduction and Motivation......Page 256
Characterizing Information and Knowledge Distribution in Large Organizations......Page 257
Defeasible Argumentation with DeLP......Page 258
Modelling Hierarchies and Policies with DeLP......Page 260
A Case Study: Distributing Memos in ACME Inc.......Page 261
Characterizing Organization Knowledge......Page 262
Solving Conflicts for Information Distribution as DeLP Queries......Page 263
Conclusions......Page 266
Introduction......Page 269
Causal Graphs......Page 270
Cartwright’s Criticism of the Markov Condition in Causal Graphs......Page 271
Acknowledgements......Page 278
References......Page 279
Introduction......Page 280
Dimensionality Reduction......Page 281
Constructive Induction......Page 282
PCA......Page 283
The Random Projection Approach......Page 284
Class-Conditional Eigenvector-Based FE......Page 285
Experiments and Results......Page 286
Conclusions......Page 289
References......Page 290
Introduction......Page 292
Related Work......Page 294
Size of Neighborhood and Attribute Dependences......Page 295
A Learning Algorithm Based on Instance Cloning......Page 296
Experimental Methodology and Results......Page 297
Conclusions......Page 301
Characteristics of the Data Sets......Page 304
Evaluation Methods......Page 305
Comparisons of the Four DRTs......Page 306
Conclusions and Future Work......Page 307
References......Page 308
Introduction......Page 309
The Select Operator......Page 310
With Evidence Potentials......Page 311
Advantages of Processing Evidence with the Select Operator......Page 312
References......Page 313
Introduction......Page 314
Spatial Outliers and Related Notions......Page 315
DBSODRS Algorithm......Page 316
Experimental Evaluation......Page 317
References......Page 318
Introduction......Page 319
Related Work......Page 320
Three Observations......Page 321
Relations in Indexes......Page 322
Lexical Classes......Page 325
Sample Results......Page 326
Current Limitations......Page 328
References......Page 329
Introduction......Page 331
Related Work......Page 332
Space-Reduction Heuristics for Candidate Acronyms......Page 335
Space-Reduction Heuristics for Candidate Definitions......Page 336
Acronym-Definition Features for Supervised Learning......Page 337
Experimental Results......Page 338
The Parenthesis Feature......Page 339
Conclusion......Page 340
References......Page 341
Adjective Hierarchy: The Conventional View......Page 342
Fake Guns Are Guns......Page 344
Equality in Typed Sets......Page 346
Examples Using the New Approach......Page 347
Multiple-Adjectives-One-Head-Noun Combinations......Page 348
Consequences......Page 351
References......Page 352
Introduction......Page 354
Related Work......Page 355
Parsed Corpus Frequencies......Page 356
Web Frequencies......Page 357
Modelling Gender Information......Page 358
The Data Sets......Page 359
Testing Gender Classification......Page 360
Pronoun Resolution with Enhanced Gender......Page 361
Robust Anaphora Resolution......Page 362
Conclusion......Page 364
Introduction......Page 366
Methodology......Page 367
Content-Based Metrics......Page 368
Decision Process......Page 369
Corpus......Page 370
Results......Page 371
Real World Task......Page 372
Evaluation Protocol......Page 373
Results......Page 374
Future Work and Conclusions......Page 375
Introduction......Page 378
Rule Induction Approaches......Page 379
Lexical and Contextual Tagging......Page 380
Learning Rules to Correct Complex Tagging Errors......Page 381
Extraction of Terms......Page 382
Part-of-Speech Tagging......Page 383
Influence of PoS-Tagging on the Terminology......Page 384
General Discussion......Page 385
Conclusion......Page 386
References......Page 387
Introduction......Page 389
Relevant Literature......Page 390
Proposed Method......Page 391
Cooccurrence Analysis......Page 392
Chi-Square Test Overview......Page 393
Experimental Settings......Page 394
Results......Page 396
Conclusion and Future Work......Page 398
Introduction......Page 401
The Task: Text Chunking......Page 402
Multiple Data Representations......Page 403
The Inside/Outside Representation......Page 404
Specialized Data Representation......Page 405
Voting Between Multiple Representations......Page 407
Arbitrary Phrase Identification (CoNLL-2000)......Page 408
Runtime Performance......Page 409
Significance Testing......Page 410
Conclusion......Page 411
References......Page 412
Introduction......Page 413
An Architecture for a Public-Domain SpeechWeb......Page 414
A Browser for a Public-Domain SpeechWeb......Page 415
References......Page 417
The Transcription......Page 418
The Syllabication......Page 419
The Concatenation......Page 420
The Results of Tests......Page 421
References......Page 422
Translation of Prepositions: Looking into Use Types......Page 424
Experimentation and Results......Page 426
Conclusion and Future Work......Page 427
References......Page 428
Related Work......Page 429
Implementation......Page 430
Conclusion and Future Work......Page 432
Introduction......Page 434
Headline Generation......Page 435
Evaluation......Page 436
Conclusion and Future Work......Page 437
Introduction......Page 439
RLSC Theory......Page 440
Experiments with RBF Kernel......Page 441
Experiments with the Reduced RBF Kernel......Page 442
References......Page 443
Introduction......Page 444
A Brief Overview of Dynamic Bayesian Networks......Page 445
Language Modeling with DBNs......Page 446
Experiments......Page 447
Conclusion......Page 448
Introduction......Page 450
Background on TD......Page 451
Background on MCMI......Page 452
Error Bounds of ML......Page 453
Error Bounds of MCMI......Page 455
Experiments: Comparing Estimation Accuracy......Page 456
Conclusions......Page 458
Bounding "705EP......Page 459
Belief State Value Approximation......Page 462
RTBSS Algorithm......Page 463
Experiments and Results......Page 464
Related Work and Conclusion......Page 466
Back matter......Page 468