Social Understanding (eBook)

Preface 6
Contents 8
1 Introduction: Historical Methodical and Conceptual Frames 10
1.1 Unifications of the Sciences 12
1.2 The Importance of Structural Mathematics and Computer Models 17
1.3 A Short Glossary on Complex Systems, Simulations, and Communication Theory 21
1.3.1 Complex Systems, Attractors, and Trajectories 21
1.3.2 Would-Be-Worlds: The Methods of Simulation 31
1.3.2.1 The Explanation of Complex Phenomena 33
1.3.2.2 The Prediction of the Future of a System 35
1.3.2.3 The Steering of Systems 37
1.3.3 Some Basic Concepts of Communication Theory 39
1.4 Artificial Intelligence (AI) – The Quest for a Homunculus 48
1.4.1 A Little Excursion into Science Fiction 50
1.4.2 How Much Can Eliza Understand? 61
1.4.3 Chinese Rooms, Gödel and Other Principal Arguments 68
2 The Operation Called “Verstehen”: Considerations About Formal Systematizations of Understanding 74
2.1 Understanding Versus Explanation 75
2.2 Rules and Intentions A Systematic of Interpreting 84
2.2.1 Consequences for an Understanding AI 96
2.3 The Hermeneutical Circle: The Difficult Basis of Understanding 100
2.3.1 Excursion into Simulated Detective Stories Readers 107
3 Mental Models, the Geometry of Meaning Generation, and of Information-Degrees 114
3.1 The Hermeneutical Necessity of Mental Models 117
3.1.1 A Mathematical Model 123
3.2 The Geometry of Meaning Generation 128
3.2.1 Neural Networks as Meaning Generating Systems 131
3.2.2 First Experimental Series: Training by Back Propagation 134
3.2.3 Second Experimental Series: Optimization by Genetic Algorithms 137
3.2.4 Third Series: Statistical Analysis of Large Samples 140
3.2.5 Fourth Series: The Analysis of Boolean Networks 142
3.2.6 Final Considerations 146
3.3 Information Degree and the Topology of Networks 151
3.3.1 A Final Remark with Respect to AI 159
4 The Understanding of Learning 161
4.1 Methodological Preliminary Remarks and a General Rule Schema 162
4.2 Types of Learning and the According Enforcing Rules 166
4.2.1 Supervised Learning and the According Version of the Enforcing Rule Schema 167
4.2.2 Reinforcement Learning: Of Mice and Men 172
4.2.3 Classical Conditioning: Pavlov's Dog Revisited 179
4.2.4 Self-Organized Learning: Of Juvenile Delinquents and Literary Murders 183
4.2.5 Comparative Considerations 193
4.2.6 Coming Back to AI 198
4.3 Rule Extracting or Learning from Examples 200
5 The Human Factor: Understanding Humans by Artificial Systems 209
5.1 The Origin of Restricted Perception 210
5.1.1 Classical Conditioning and the Competition Between Adidas and Nike 214
5.1.2 The Reduction of Social Perceptions to Social Darwinism 218
5.2 Understanding Readers of Detective Stories 221
5.3 The Reconstruction of Human Discourses 229
5.4 Understanding in Communicative Processes by Mental Models 241
6 Conclusions: AI and a Unified Science 251
References 259
Index 264