دانلود کتاب Agents and Artificial Intelligence 8th International Conference, ICAART 2016, Rome, Italy, February 24-26, 2016, Revised Selected Papers

فهرست مطالب :

Preface......Page 6
Organization......Page 8
Contents......Page 16
Agents......Page 18
1 Introduction......Page 19
2 Related Research on Gender and Virtual Agents......Page 21
3.1 Video Analysis of Self-adaptors......Page 22
3.2 Agent Character and Animation Implementation......Page 25
4.1 Experimental System......Page 26
4.2 Experimental Procedure......Page 27
5.1 Results of Factorial Analysis......Page 28
5.2 Analysis of Tolerance Factor and Sociability Factor......Page 29
5.3 Analysis of Gender Factor......Page 30
5.4 Analysis of Naturalness Factor......Page 31
6 Discussion and Future Directions......Page 32
References......Page 33
2 Related Work......Page 35
2.2 Planning and Model Checking......Page 37
3 Case Study: Z2......Page 38
3.1 Multiagent System Simulation......Page 39
5 Constrained Branch-and-Bound Optimization......Page 40
6 Process Synchronization......Page 44
7 Evaluation......Page 46
7.1 Inflexible Product Variants......Page 48
8 Conclusions......Page 49
References......Page 50
1 Introduction......Page 53
2 Related Work......Page 55
3.1 Agents and Tasks......Page 56
3.3 Forming Teams......Page 57
4.2 Role Selection and Learning......Page 59
4.3 Agent Switching Behavioral Strategies......Page 60
5.1 Experimental Setting......Page 61
5.2 Performance Results......Page 62
5.3 Behavioral Analysis......Page 64
5.4 Performance in Changing Environments......Page 66
5.5 Discussion......Page 68
6 Conclusion......Page 69
References......Page 70
1 Introduction......Page 72
2 Literature Review......Page 74
3 Dataset......Page 75
4 Analysis......Page 79
5 Simulation with NetLogo......Page 81
6 Conclusion......Page 85
References......Page 86
Artificial Intelligence......Page 89
1 Introduction......Page 90
2 OWL Vs Modal Representation......Page 91
3 Confidence and Confidence Intervals......Page 92
4.1 Simplification and Normal Form......Page 94
4.2 Model Theory......Page 96
4.3 Two Constraints: Well-Behaved Frames......Page 97
5 Entailment Rules......Page 98
5.1 Modal Entailments......Page 99
5.3 Extended RDFS and OWL Entailments......Page 100
6.1 Metric Linear Time......Page 102
6.2 Valid Time......Page 103
6.3 Transaction Time......Page 104
6.4 Entailment Rules for Graded Modals and Transaction Time......Page 105
6.5 Model Theory for Graded Modals and Transaction Time......Page 107
References......Page 109
1 Introduction and Motivation......Page 111
3 Background......Page 113
4 The Multi-context BDI Framework......Page 115
4.1 Belief Context......Page 116
4.2 Desire Context......Page 117
4.4 Social Context......Page 118
4.5 Planning and Intention Contexts......Page 119
4.6 Bridge Rules......Page 122
5 Illustrative Example......Page 124
6 Simulation......Page 125
7 Conclusions......Page 126
References......Page 127
1 Introduction......Page 129
2.1 Uncertainty in the Smart Grid......Page 131
2.2 Surrogate Models for der......Page 132
2.3 Decoders for Scheduling......Page 136
3 Modeling Confidence......Page 137
4 Results......Page 139
5 Conclusion......Page 143
References......Page 144
1 Introduction......Page 148
2 Related Work......Page 150
3.1 Textual Entailment......Page 151
4.1 Abstract Dialectical Frameworks......Page 153
4.2 Extracting Meaningful Information Using ADF......Page 155
5 Experimental Setting......Page 156
5.1 Dataset......Page 157
5.2 Evaluation......Page 158
6 Examples......Page 161
References......Page 163
1 Introduction......Page 166
2 Related Work......Page 168
3 Cascade of Overlapping Feature Classifiers......Page 169
4.1 Selection of Feasible Examples......Page 170
4.2 Sampling of Infeasible Examples Near the Class Boundaries......Page 172
5.1 Data Sets......Page 174
5.2 Experimental Setting......Page 176
5.3 Results......Page 177
6.1 Experimental Setup......Page 179
6.2 Results......Page 181
7 Conclusions......Page 183
References......Page 184
1 Introduction......Page 186
2.1 Min-Based Possibilistic Influence Diagrams......Page 187
3 Decomposition of Min-Based Possibilistic Influence Diagram......Page 189
3.2 Building Preference-Based Qualitative Possibilistic Network......Page 190
4.1 Qualitative Possibilistic Decision......Page 193
4.2 Computing Sequential Decisions Using Junction Trees......Page 197
5 Experimental Studies......Page 201
References......Page 202
1 Introduction......Page 204
2.1 SOM and Competitive Learning......Page 205
2.2 Flexible Structure in Neural Networks and SOM......Page 209
3.1 Phase I: AMSOM Initialization......Page 210
3.2 Phase II: Training......Page 213
3.3 Phase III: AMSOM Finalization and Clustering of the Map......Page 217
4 Experiments......Page 219
5 Conclusion......Page 223
References......Page 224
1 Introduction......Page 227
2 Related Research......Page 229
3.1 Recognizing Multi-agent Plans......Page 230
3.2 Extending PRAP to Teams......Page 231
4.1 A Team Blocks World Domain......Page 234
4.2 Multi-agent Plan Synthesis......Page 235
5.1 Efficiency of Pruning......Page 236
5.2 Precision of Recognition......Page 237
5.3 Accuracy of Recognition......Page 239
7 Conclusions......Page 241
References......Page 242
1 Introduction......Page 244
2 Syntax and Semantics of EL+......Page 246
3.1 Computation of T*......Page 247
3.2 Computation of A*......Page 249
4 Secrecy-Preserving Reasoning in EL+ KBs......Page 252
5 Query Answering......Page 256
References......Page 260
1 Introduction......Page 262
2 Background......Page 263
3 The Proposed Approach......Page 264
3.1 Generating Triangular Membership Functions......Page 265
3.2 Generating Trapezoidal Membership Functions......Page 266
4.1 Dataset......Page 268
4.2 Comparison of Techniques for Parameterizing Attributes with Different Characteristics......Page 269
4.3 Results on Classification Accuracy Using MFs Produced by Different Techniques......Page 274
5 Conclusion......Page 277
References......Page 278
1 Introduction......Page 280
2 Related Research......Page 281
3.1 Problem Description......Page 282
3.2 Protocol Description of Public ACCORD......Page 283
3.3 Protocol Description of Private ACCORD......Page 285
4.1 Experimental Methodology......Page 286
4.2 Fair/Selfish Behaviour in Public ACCORD......Page 288
4.3 Cooperative/Uncooperative Behaviour in Public ACCORD......Page 289
4.4 Fair/Selfish Behaviour in Private ACCORD......Page 291
4.5 Cooperative/Uncooperative Behaviour in Private ACCORD......Page 293
References......Page 296
1 Introduction......Page 298
2.1 The AVS Model......Page 301
2.2 The rAVS Model......Page 303
3 Model Comparison......Page 305
3.1 Goodness-Of-Fit (GOF)......Page 306
3.2 Simple Hold-Out (SHO)......Page 307
3.3 Model Flexibility Analysis (MFA)......Page 308
3.4 Discussion......Page 310
4 Conclusion......Page 311
4.1 Future Work......Page 312
References......Page 314
1 Introduction......Page 317
2 Proposed Approach......Page 319
3 Experiments and Discussion......Page 322
References......Page 326
Author Index......Page 329