Contents

pp v-viii

Preface

pp ix-xi

Acknowledgements

pp xii-xii

Introduction: Living Systems, Causality, and Information

pp 1-6

Part I - Preliminaries

pp 7-8

1 - A Computational Approach to Causality

pp 9-53

2 - Networks: From Structure to Dynamics

pp 54-94

3 - Information and Computability Theories

pp 95-138

Part II - Theory and Methods

pp 139-140

4 - Algorithmic Information Theory

pp 141-177

5 - The Coding Theorem Method (CTM)

pp 178-188

6 - The Block Decomposition Method (BDM)

pp 189-213

7 - Graph and Tensor Complexity

pp 214-227

8 - Algorithmic Information Dynamics (AID)

pp 228-240

Part III - Applications

pp 241-242

9 - From Theory to Practice

pp 243-250

10 - Algorithmic Dynamics in Artificial Environments

pp 251-262

11 - Applications to Integer and Behavioural Sequences

pp 263-273

12 - Applications to Evolutionary Biology

pp 274-297

Postface

pp 298-298

Appendix: - Mutual and Conditional BDM

pp 299-307

Glossary

pp 308-309

References

pp 310-321

Index

pp 322-332