AI*IA 2005: Advances in Artificial Intelligence: 9th Congress of the Italian Association for Artificial Intelligence Milan, Italy, September 21-23,

Front matter......Page 1
Introduction......Page 14
Definitions......Page 15
General Results......Page 18
Complexity of Action Redundancy......Page 19
Related Work......Page 23
Conclusions......Page 24
Introduction......Page 26
Preliminaries......Page 27
Small-World SAT Instances......Page 28
Experimental Results......Page 32
Conclusion and Future Work......Page 35
Introduction......Page 38
$CSM$, A Model for Commonsense Spatial Reasoning......Page 40
Reasoning into Space: An Hybrid Logic Approach......Page 42
Spatial Reasoning with Hybrid Logic......Page 44
A Hybrid Logic for Commonsense Spatial Reasoning......Page 48
Concluding Remarks......Page 49
Introduction......Page 51
Preliminaries......Page 53
Definitions......Page 54
Experiments with the Theorem Prover......Page 55
Definitions......Page 59
Experiments with the Theorem Prover......Page 60
Conclusions and Current Research......Page 61
Introduction......Page 63
Running Example......Page 64
Common Traps......Page 65
Concatenation of Columns......Page 66
Concatenation of Values......Page 68
Existential First-Order Features......Page 69
Cardinalities......Page 70
Multiple-Instance Problems......Page 71
Strengths and Weaknesses......Page 72
Conclusion......Page 73
Representing Periodicity-Based Constraints......Page 75
Extensional and Intensional Calculi......Page 76
References......Page 78
Fitness Distance Correlation......Page 79
Structural Mutations......Page 80
Unimodal Trap Functions......Page 81
Royal Trees......Page 82
Counterexample......Page 83
Sampling Methodology......Page 84
Definition of the $nsc$......Page 85
The Binomial-3 Problem......Page 86
The Even Parity $k$ Problem......Page 87
Conclusions and Future Work......Page 88
Documents Representation......Page 91
Learning WordNet-Based User Profiles......Page 92
Experimental Results......Page 94
Introduction......Page 95
Refined Approximations......Page 96
Algorithms of Finding the Multielement Bounds......Page 97
Conclusion......Page 98
Introduction......Page 99
Arguments for Policies and Objectives......Page 101
Argumentation Theory for Interactive Access Control......Page 106
Related Research......Page 108
Concluding Remarks......Page 109
Introduction......Page 111
Value-Based Argumentation Framework......Page 113
Development of a Position......Page 114
Dialogue Framework......Page 115
Checking Conflict-Freeness......Page 116
Making the Arguments Acceptable......Page 117
Development of Positions......Page 119
Related Work and Conclusion......Page 121
Introduction......Page 123
Related Works......Page 125
The Backtracking Strategy......Page 126
One Target Concept Made Up of More Than One Clause......Page 127
Implementation in INTHELEX......Page 128
Experiments......Page 131
Experimental Results......Page 132
Conclusions and Future Works......Page 133
Introduction......Page 135
Answer Set Programming......Page 137
cmodels2 and assat: SAT-Based Answer Set Programming......Page 138
Relation with smodels......Page 139
Experimental Analysis......Page 140
Tight Logic Programs......Page 142
Non-Tight Logic Programs......Page 144
Conclusions......Page 145
Introduction......Page 148
Knowledge Representation......Page 150
Declarative Semantics......Page 152
Data Structures......Page 153
Transitions......Page 154
Related Work......Page 157
Conclusions......Page 158
Introduction......Page 161
Task Description......Page 162
Temporal Precedence Graph......Page 163
Planning Structure......Page 164
Constraint Propagation Algorithm......Page 165
Probabilistic Temporal Planning......Page 166
Execution Probability, Total Cost and Total Time......Page 167
Selection of the Most Likely Admissible Plan......Page 168
Reducing the Number of Intervals......Page 169
Illustrative Example......Page 170
Conclusion......Page 171
Introduction......Page 173
Scheduling with Uncertainty and Partial Order Schedules......Page 174
$Solve-and-Robustify$......Page 177
Generating Flexible Schedules from Different Initial Solutions......Page 179
Experimental Evaluation......Page 180
Discussion: Makespan Versus Robustness......Page 182
Conclusions......Page 184
The Search Space of Active Schedules......Page 186
The A* Algorithm......Page 187
Experimental Results......Page 188
References......Page 189
Derived Predicates and Rule Graph......Page 190
Rule-Action Graphs......Page 191
Local Search Techniques for Rule-Action Graphs......Page 192
Experimental Results......Page 193
Introduction......Page 195
The Path-Planner Architecture......Page 196
Conclusion......Page 198
Introduction......Page 199
Basic Modalities for MAS......Page 200
Henkin Quantifiers......Page 201
Henkin Quantifiers Revisited......Page 203
Henkin's Isolated Agents......Page 204
Risk-Averse Coordinated Agents......Page 206
Knowing the Past, Reasoning About the Future......Page 207
Related Work and Conclusions......Page 208
Introduction......Page 211
Role-Based Access Control: An Overview......Page 212
Moving RBAC to Multi-agent Systems......Page 213
Sessions and ACCs......Page 214
Agent Interaction with ACCs......Page 215
Notation and Syntax......Page 216
Operational Semantics......Page 218
Related Work and Conclusions......Page 222
Introduction......Page 225
An Alternative to Formal Concepts in Noisy Data Sets......Page 227
Experiments on Data Plus Noise......Page 230
Conclusion......Page 235
Introduction......Page 237
Illustrative Scenarios......Page 238
A Multi-agent Architecture......Page 239
Formal Definitions......Page 240
Connecting the Physical World with Software Agents......Page 241
Software Agents for Physical Components......Page 242
A Concrete Negotiation Protocol......Page 244
Related Work......Page 246
Conclusions, Discussion and Future Work......Page 247
Introduction......Page 250
Knowledge-Level Description......Page 251
Architectural-Level Description......Page 256
The Contract Net Protocol......Page 258
Properties of the Contract Net......Page 259
Related Work and Conclusions......Page 260
Introduction......Page 262
The Hierarchical Hidden Markov Model......Page 263
Algorithm Overview......Page 264
Evaluation on Artificial Traces......Page 265
Text Typing Model......Page 267
Conclusion......Page 269
Introduction......Page 271
Preliminary Definitions and Notation......Page 272
Description and Construction of the BHF......Page 275
Description of the Incremental Algorithm......Page 276
Results......Page 277
Conclusions......Page 280
Introduction......Page 283
Preliminaries: Automata and Trajectories......Page 284
Automata Chain......Page 285
Diagnosis by Slices......Page 289
Incremental Diagnosis......Page 290
Temporal Windows Diagnosis......Page 291
Conclusion......Page 293
Motivation......Page 295
Formal Development......Page 297
Inferring Causal Predictions and Explanations......Page 298
Motivations and Formalization......Page 299
An Example......Page 300
Conclusions and Future Work......Page 302
Introduction......Page 303
A Semantic Similarity Measure......Page 305
A $semantic$ Vector Space......Page 307
Support Vector Machines and Kernel Methods......Page 308
Experimental Set-Up......Page 309
Cross Validation Results......Page 310
Related Work......Page 312
Conclusions......Page 313
Introduction......Page 316
LTAG, Dynamic Grammars and DVTAG......Page 317
Building a Wide Coverage DVTAG......Page 320
Left-Association......Page 321
Converting an Automatically Extracted LTAG into a DVTAG......Page 322
Extraction of an English DVTAG from Penn Treebank......Page 323
Extraction of an Italian DVTAG from TUT......Page 325
Conclusions......Page 326
Introduction......Page 328
Definitions......Page 329
Type of Entailment......Page 330
Graph Matching and XDG Basic Concepts......Page 331
Adapting XDG and Graph Matching to Textual Entailment......Page 332
Graph Syntactic Similarity Measure for Textual Entailment......Page 334
Experimental Setting and Result Analysis......Page 337
Conclusions and Future Works......Page 339
Multigranular Automatic Recognition......Page 340
References......Page 343
Introduction......Page 344
Context and Related Work......Page 345
Formal Description......Page 346
Applicability of the Proposed Approach......Page 350
A Case Study: P-Truck Curing......Page 351
Curing Process Adaptation......Page 353
Conclusions and Future Developments......Page 354
Introduction......Page 356
Transaction Analyzer......Page 357
Plan Predictor......Page 358
References......Page 359
Introduction......Page 360
Keystroke Analysis......Page 361
Computing the Distance Between Two Typing Samples......Page 362
Gathering of the Typing Samples......Page 364
User Identification......Page 365
User Authentication......Page 366
Discussion and Applications......Page 367
Conclusion......Page 370
Introduction......Page 372
Knowledge Space Theory......Page 374
The Proposed Methodology......Page 375
System Implementation and Results......Page 379
Conclusions......Page 381
Introduction......Page 383
Goals of the Project and Choices for Semantic Knowledge Representation......Page 384
Description of the Framework......Page 385
An Example of Application of the Framework......Page 390
Conclusion and Related Work......Page 392
References......Page 393
Introduction......Page 394
Theoretical Background: The LSA Paradigm......Page 396
A Proposal of a ``Conceptual" Interpretation of the Semantic Space......Page 397
An Example of ``Conceptual" Axis Tagging......Page 398
Data-Driven Conceptual Space Creation......Page 400
Experimental Results and Comparison with Alice......Page 401
Conclusions and Future Work......Page 404
Introduction......Page 406
Using the Web for Clue-Answering: The Web Search Module......Page 407
Retrieving Useful Documents......Page 409
Extracting and Ranking the Candidates......Page 410
The Statistical Filtering......Page 411
The Morphological Filtering......Page 413
The Other Modules......Page 415
Experimental Results......Page 416
Conclusions......Page 417
Introduction......Page 419
Background......Page 420
Learning Through Refinement Operators......Page 422
Properties......Page 423
Operators Depending on Examples......Page 424
The Algorithm: Implementing the Operators......Page 425
Experimentation......Page 426
Conclusions and Further Developments......Page 429
Introduction......Page 431
Application of Mr-SBC......Page 433
Application of ATRE......Page 436
Experiments......Page 437
Conclusions......Page 440
References......Page 441
Introduction......Page 443
Related Work......Page 444
Handling Continuous-Valued Data in an Incremental FOL Learning System......Page 446
Modification to the Object Identity Framework......Page 447
Refinement Operators......Page 448
Experiments......Page 451
Conclusion and Future Works......Page 453
Introduction......Page 455
State of the Art......Page 456
The AmI Framework Technological Approach......Page 457
The AmI Framework General Architecture......Page 459
The AmI Core......Page 460
The Results......Page 464
Conclusions and Future Work......Page 465
Introduction......Page 467
Representation Formalism......Page 468
Acquisition and Execution Tools......Page 469
Decision Making......Page 470
Contextualization to the Software Environment: GLARE’s Three-Layered Architecture......Page 471
Guidelines’ Resource-Based Contextualization......Page 472
Clinical Guidelines Local Adaptations and Updates......Page 473
Managing Authors and Multiple Versions......Page 474
Comparisons, Conclusions and Future Work......Page 476
References......Page 477
A New MAS / GIS DSS Approach......Page 479
DSS Architecture and Implementation......Page 480
Experimentations......Page 481
References......Page 482
Introduction......Page 483
Chord Fingering Modeled Via CSP......Page 484
Preliminary Experiment and Conclusions......Page 485
Introduction......Page 487
Remarks of the Adopted Theoretical Framework......Page 488
The Cognitive Architecture of the Robot......Page 489
The Vision System......Page 491
Human-Robot Interactions......Page 493
CiceRobot at Work......Page 494
References......Page 495
Introduction......Page 496
Rescue Scenario......Page 497
Human Robot Interaction and Mixed Initiative Planning in Rescue Arenas......Page 498
Control Architecture......Page 499
Model-Based Monitoring......Page 500
Mixed-Initiative Planning......Page 503
Mixed-Initiative Approach at Work......Page 504
Conclusion......Page 506
Introduction......Page 508
The Cognitive Architecture......Page 509
The Subconceptual Area......Page 510
The Conceptual Area......Page 511
Learning, Anchoring and Imitation in the Architecture......Page 512
Processing in the Subconceptual Space......Page 513
Representation in Conceptual Spaces......Page 514
Learning in the Architecture......Page 515
Anchoring in the Architecture......Page 516
Imitating in the Architecture......Page 517
References......Page 518
Introduction......Page 520
Fusing with Bayesian Programming......Page 521
Architecture Proposed......Page 522
Emotional Modules......Page 523
Experimental Validation......Page 527
Conclusions......Page 529
Introduction......Page 531
Data Fusion and Incoherence Detection......Page 532
Conclusions......Page 533
Introduction......Page 535
System Architecture......Page 537
Relational Association Rules Mining......Page 539
Transforming Association Rules in Boolean Features......Page 540
Experimental Results......Page 542
Conclusions......Page 545
References......Page 546
The Deep Web......Page 548
Natural Language Querying......Page 550
Operation of NL Module......Page 551
The Entity Recognizer......Page 552
Examples......Page 555
Conclusions......Page 558
Introduction......Page 560
Characteristics of Korean Grammatical Function Words......Page 561
Automatic Detection of Korean Accentual Phrase Boundaries......Page 562
Experiment......Page 563
Results......Page 564
References......Page 565
Introduction......Page 566
Overview of the Two Fuzzy Approaches......Page 567
Multivariate Probability Approach......Page 568
Numerical Example......Page 569
Multivariate Fuzzy Quality Control Chart: MFQCC......Page 570
Multivariate Attribute Quality Control Charts: MAQCC......Page 573
Conclusion......Page 575
Introduction......Page 577
Fuzzy Sets and Logic......Page 578
Subtrees of the RM......Page 580
Experiments......Page 585
Summary......Page 587
References......Page 588
Introduction......Page 589
Land-Use and Transportation Model......Page 590
Parametric Study......Page 592
Fitness Function......Page 593
Parallel Genetic Algorithm Design......Page 594
Case Study......Page 595
References......Page 598
Introduction......Page 600
Related Work......Page 601
Agents in Bioinformatics......Page 602
The PACMAS Architecture......Page 603
Agents for Predicting Protein Secondary Structures......Page 605
Preliminary Experimental Results......Page 608
Conclusions and Future Work......Page 609
Introduction......Page 612
MK: A Markovian Post-processing Method......Page 613
References......Page 615
Electrically Heated Micro Heat Exchanger......Page 616
Locally Linear Model Tree Identification of Nonlinear Systems......Page 617
Predictive Controller Design......Page 618
References......Page 619
Introduction......Page 621
Framework Model......Page 622
Conclusions and Future Works......Page 623
Back matter......Page 625