Natural and Artificial Reasoning: An Exploration of Modelling Human Thinking


Natural and Artificial Reasoning: An Exploration of Modelling Human Thinking (2014) .. by Tom Addis


Contents

1 Insight and Reason … 1
1.1 Introduction … 1
1.2 Testing for Intelligence … 3
1.2.1 The Imitation Game … 3
1.3 Intelligence Tests… 5
1.4 Discontinuity Theory … 7
References … 10

2 Information and Intelligence … 13
2.1 Introduction … 13
2.2 Information … 13
2.3 Insight. … 17
2.3.1 The Distinction Between Information and Knowledge . . 18
2.4 Induction … 19
2.5 Deduction … 21
2.6 Lookup or Generate? … 23
References … 25

3 Identifying Intelligence … 27
3.1 Introduction … 27
3.1.1 Stone Soup: A Folk Story … 27
3.2 Uncertainty … 28
3.3 Selecting an Action … 28
3.4 Nature’s Intelligence … 38
References … 41

4 Knowledge Science … 43
4.1 Introduction … 43
4.2 A Taxonomic Approach … 44
4.2.1 Tacit Knowledge … 47
4.2.2 Declarative Knowledge … 47
4.2.3 Heuristic Knowledge … 49
4.2.4 Inferential Knowledge … 49
4.3 Intelligent Inference … 51
4.4 Knowledge Acquisition … 53
4.4.1 Abstracting to a Representation … 53
4.5 Knowledge as Data and Processing … 55
4.6 The Boundaries of Knowledge Representation … 57
References … 58

5 Modelling Experiments … 61
5.1 Introduction … 61
5.2 Experiment, Inference and Theory Change … 62
5.2.1 Experiments and Experimenters … 62
5.3 Rationality, Inference Rules and Epistemic Practices … 63
5.4 Dynamic, Socially Mediated Inference … 64
5.5 Experiments as Mediating Models … 66
5.6 Static and Iterative Models. … 67
5.7 Abductive Systems in Science … 68
References … 70

6 Modelling Inference … 73
6.1 Simulation Methods … 73
6.2 Confidence Adjustment … 74
6.3 The Impact of Evidence: Hypotheses … 75
6.4 The Impact of Opinion: Consultation … 76
6.5 A Simple Example of Confidence Adjustment … 76
6.6 Confidence, Indifference and Change … 78
6.7 Agents and Groups … 81
6.8 The Choice of an Action … 81
6.8.1 Evaluating Actions … 81
6.9 Choosing Actions … 84
6.10 Running the Program … 86
6.11 Other Examples … 87
6.12 Belief and Truth … 88
References … 89

7 Simulating Belief and Action … 91
7.1 Modelling Inferences About Observations … 91
7.2 Why Inference Can’t be Modelled. … 93
7.3 A Historical Example … 95
7.4 Simulating Experimental Science … 98
7.5 How Experiments Mediate Between Hypotheses and Phenomenology … 98
7.6 Evidence-Driven Belief-Revision … 100
7.6.1 Non-consultation Run (Solo) … 101
7.6.2 Consultation Run for Two Agents (Actor1 & 2) … 101
7.7 Conclusions … 103
References … 106

8 Programming and Meaning … 107
8.1 A Grand Challenge … 107
8.1.1 Meeting the Criteria … 108
8.1.2 Problems with Referential Semantics. … 110
8.2 Inferring Internal Experience … 111
8.3 A Philosophical Paradigm of Meaning for Computing … 112
8.3.1 Objects. … 113
8.3.2 A Rational Set … 115
8.3.3 Social Consequences … 117
References … 117

9 Irrational Reasoning … 119
9.1 Dual Semantics … 119
9.2 The Paradigm Leap … 121
9.3 Examples of Irrational Sets … 122
9.3.1 The Problem of Rules … 122
9.3.2 The Problem of Irrational Sets … 123
9.3.3 Some Predictions from this Thesis … 124
9.4 Inferential Semantics … 125
9.5 The Real Challenge … 126
9.6 A Science of Mechanisms … 127
References … 128

10 Knowledge for Design … 129
10.1 Knowledge-Based Systems … 129
10.2 The Role of a Model … 133
10.3 The Limits of Logic … 137
References … 140

11 Measures of Intelligence … 141
11.1 IQ as a Measure of Intelligence … 141
11.2 Sequence Extrapolation as a Model … 143
11.3 Learning in Retroduction and Induction … 144
11.4 The Basic Concepts. … 145
11.4.1 INTER … 145
11.4.2 PERIODIC … 147
11.4.3 POLY … 148
11.4.4 PRIME. … 150
11.4.5 FACTORIAL … 151
References … 151

12 Implementing Intelligence … 153
12.1 Features of Intelligence … 153
12.2 Implementation of Intelligence … 154
12.2.1 The Deductive Process. … 158
12.2.2 The Inductive Process … 159
12.3 Feedback Assessment … 159
12.4 Experiments and Discussion … 160
12.5 Conclusion … 163
12.5.1 Intelligence Quality Specification … 163
References … 164

13 Figuratively Speaking … 165
13.1 The Problem with Reference … 165
13.2 Tropic Communication … 166
13.3 The Conceptual Model … 167
13.4 The Functional Model. … 168
13.4.1 Background … 168
13.5 The Initial Model. … 169
13.6 The Abstracted Initial Model … 171
13.7 The Basic Functional Model … 173
13.8 A Commented Run of the Model … 178
13.9 The Single Experience … 179
13.10 Consult … 179
13.11 Future Development … 180
13.12 Conclusions … 181
References … 181

14 Seeking Allies … 183
14.1 Exchanging Information … 183
14.2 The Experiment … 184
14.3 The Computer Model … 185
14.4 Analysis of the Experimental Results … 186
14.5 Model Running Results Analysis … 189
14.6 Model Data Input and Results Analysis … 190
14.7 Assessing the Results … 193
14.8 Ally Choice … 195
14.9 Last Words … 196
References … 198

 

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