Collaboration between Human and Artificial Societies

41WY1iqpZQL......Page 1
front-matter......Page 2
01......Page 16
Conclusions and Future Work......Page 0
02......Page 43
Introduction......Page 56
Fuzzification of Theories......Page 57
Classification of Quantitative and Qualitative Application Characteristics......Page 59
Configuration in Multiple-Strategy and/or Multiple-Application/Multiple-Target Environments......Page 60
Performance Ranges......Page 62
Data Distributions......Page 64
Classification of Approaches......Page 65
Performance Monitoring......Page 66
Multiple Passes and Hierarchical Organization......Page 68
Philosophical Excursion......Page 71
Summary and Future Prospects......Page 72
04......Page 75
Introduction......Page 87
Learning as a side effect of communication......Page 89
Types of communication......Page 90
Agent communication languages: KQML......Page 91
The STROBE model......Page 92
Informal description of interactions......Page 93
The lexicon......Page 94
OBjects......Page 95
Simple classification of moves......Page 96
Multiple contexts......Page 98
Emerging functionality’s......Page 99
Our KQML extension: supporting richer pragmatic primitives......Page 100
Code excerpts......Page 101
Autonomous agents are not just pair-wise communicating......Page 103
The coordination of message exchanges in multi-agent dialogues......Page 105
STROBE agents versus Actors......Page 106
Metaphors for communication: telephone versus mail......Page 107
The explicit representation of state changes in STROBE agents......Page 108
Conclusions......Page 109
References......Page 110
Acknowledgements......Page 112
06......Page 115
Introduction......Page 126
DAI Approach to Problem Solving......Page 127
Using Actor Model......Page 130
Concurrent Diagnostic Reasoning about Mental States......Page 131
TermActors......Page 132
Sewer-Actors......Page 133
Example......Page 134
Concurrent Diagnostic Reasoning about Physical States......Page 137
Conclusions......Page 140
08......Page 143
Introduction......Page 153
The CBR Agent Environment: Wastewater Treatment Plants......Page 154
The Target System: A Hybrid Multi-knowledge Supervisory Architecture......Page 155
Static Problems with a CBR Agent......Page 156
Our CBR Approach......Page 157
Bad Performance in Space......Page 160
Bad Performance in Time......Page 162
Unsuccessful Search in the Case Library......Page 163
The Extended CBR Agent Cycle......Page 164
Preliminary Experimental Evaluation......Page 166
Conclusions and Future Work......Page 167
10......Page 170
11......Page 193
12......Page 209
13......Page 228
14......Page 242
15......Page 254
Introduction......Page 272
User Interface......Page 274
Watching User™s Navigations behind the Scene......Page 275
Detailed Architecture......Page 277
Cases Indexed by a Time-Extended Situation......Page 278
Representation of a WWW Navigation......Page 279
Navigational Cases......Page 280
Reusing Past Navigations......Page 281
Retrieval Alternatives......Page 282
Similarity Measures......Page 283
Case Reuse......Page 284
Case-Based Browsing Advisors......Page 285
Synthesis......Page 286
Experimental Evaluation......Page 287
Conclusion......Page 288
17......Page 292
back-matter......Page 309