Samson Abramsky on Logic and Structure in Computer Science and Beyond
Samson Abramsky’s wide-ranging contributions to logical and structural aspects of Computer Science have had a major influence on the field. This book is a rich collection of papers, inspired by and extending Abramsky’s work. It contains both survey material and new results, organised around six majo...
Other Authors: | , |
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Format: | eBook |
Language: | English |
Published: |
Cham
Springer International Publishing
2023, 2023
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Edition: | 1st ed. 2023 |
Series: | Outstanding Contributions to Logic
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Subjects: | |
Online Access: | |
Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Chapter 8. An axiomatic account of a fully abstract game semantics for general references (Jim Laird and Guy McCusker)
- Chapter 9. Deconstructing general references via game semantics (Andrzej S. Murawski and Nikos Tzevelekos)
- Chapter 10. The game semantics of game theory (Jules Hedges)
- Part 3. Contextuality and quantum computation
- Chapter 11. Consistency, acyclicity, and positive semirings (Albert Atserias and Phokion G. Kolaitis)
- Chapter 12. Closing bell, boxing black box simulations in the resource theory of contextuality (Rui Soares Barbosa, Martti Karvonen, and Shane Mansfield)
- Chapter 13. Describing and animating quantum protocols (Richard Bornat and Rajagopal Nagarajan)
- Chapter 14. The Contextuality-by-default view of the Sheaf-Theoretic approach to contextuality (Ehtibar Dzhafarov)
- Chapter 15. Godel, Escher, Bell, contextual semantics for logical paradoxes (Kohei Kishida)
- Part 1. Duality and domains in logical form
- Chapter 1. Duality, intensionality, and contextuality: Philosophy of category theory and the categorical unity of science in Samson Abramsky (Yoshihiro Maruyama)
- Chapter 2. Minimisation in logical form (Nick Bezhanishvili, Marcello Bonsangue, Helle Hvid Hansen, Dexter Kozen, Clemens Kupke, Prakash Panangaden, and Alexandra Silva)
- Chapter 3. A Cook’s tour of duality in logic: From quantifiers, through Vietoris, to measures (Mai Gehrke, Tomas Jakl, and Luca Reggio)
- Chapter 4. Stone duality for relations (Alexander Kurz, Andrew Moshier, and Achim Jung)
- Part 2. Game semantics
- Chapter 5. The mays and musts of concurrent strategies (Simon Castellan, Pierre Clairambault, and Glynn Winskel)
- Chapter 6. A tale of additives and concurrency in game semantics (Pierre Clairambault)
- Chapter 7. The far side of the cube: An elementary introduction to game semantics (Dan Ghica)
- Chapter 16. Putting paradoxes to work: Contextuality in measurement-based quantum computation (Robert Raussendorf)
- Part 4. Game comonads and descriptive complexity
- Chapter 17. Monadic Monadic second order logic (Mikolaj Bojanczyk, Bartek Klin, and Julian Salamanca)
- Chapter 18. Constraint satisfaction, graph isomorphism, and the pebbling comonad (Anuj Dawar)
- Chapter 19. The strategic balance of games in logic (Jouko Vaananen)
- Part 5. Categorical and logical semantics
- Chapter 20. Compositionality in context (Alexandru Baltag, Johan van Benthem, and Dag Westerstahl)
- Chapter 21. Compact inverse categories (Robin Cockett and Chris Heunen)
- Chapter 22
- Reductive logic, proof-search, and Coalgebra: A perspective from resource semantics (Alexander Gheorghiu, Simon Docherty, and David Pym)
- Chapter 23. Lambek-Grishin calculus: Focusing, display and full polarization (Giuseppe Greco, Michael Moortgat, Valentin D. Richard, and Apostolos Tzimoulis)
- Chapter 24. On strictifying extensional reflexivity in compact closed categories (Peter Hines)
- Chapter 25
- Semantics for a Lambda calculus for string diagrams (Bert Lindenhovius, Michael Mislove, and Vladimir Zamdzhiev)
- Chapter 26. Retracing some paths in categorical semantics: From process-propositions-as-types to categorified reals and computers (Dusko Pavlovic)
- Part 6. Probabilistic computation. Chapter 27. (Towards a) Statistical probabilistic Lazy Lambda calculus (Radha Jagadeesan)
- Chapter 28. Multisets and distributions, in drawing and learning (Bart Jacobs)
- Chapter 29. Structure in machine learning (Prakash Panangaden)