Abstract
This paper connects three concepts in computer science, zero-knowledge proofs, causal reasoning, and bisimulation, to show that interaction is more powerful than observation. Observation is the use of input data plus, possibly, tractable computation, in such a way that the observer has no effect on the source of the data. Interaction is observation plus action that affects the source of the data. Observation lets the data “speak for itself” and is objective, whereas interaction is first-person and subjective. Zero-knowledge proofs are a strategy for building confidence in some fact while acquiring no additional information other than that the fact is likely to be true. They fall short of absolute certainty and they require interaction. This paper shows that absolutely certainty for such scenarios can be modeled by a bisimulation relation. Causal reasoning has also been shown to require subjective involvement. It is not possible by observation alone, and like zero-knowledge proofs, requires first-person involvement and interaction. This paper shows that bisimulation relations can reveal flaws in causal reasoning.
This work was supported in part by the National Science Foundation, NSF award #1446619 (Mathematical Theory of CPS).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Sangiorgi gives a nice overview of the historical development of this idea [15]. He notes that essentially the same concept of bisimulation had also been developed in the fields of philosophical logic and set theory.
References
Agha, G.A.: Abstracting interaction patterns: a programming paradigm for open distributed systems. In: Najm, E., Stefani, J.B. (eds.) Formal Methods for Open Object-based Distributed Systems. IFIPAICT, pp. 135–153. Springer, Heidelberg (1997). https://doi.org/10.1007/978-0-387-35082-0_10
Babai, L.: Trading group theory for randomness. In: Symposium on Theory of Computing (STOC), pp. 421–429. ACM (1985). https://doi.org/10.1145/22145.22192
Black, H.S.: Stabilized feed-back amplifiers. Electr. Eng. 53, 114–120 (1934)
Goldin, D., Smolka, S., Attie, P., Sonderegger, E.: Turing machines, transition systems, and interaction. Inf. Comput. 194(2), 101–128 (2004)
Goldwasser, S., Micali, S., Rackoff, C.: The knowledge complexity of interactive proof systems (extended abstract). In: Symposium on Theory of Computing (STOC), pp. 291–304. ACM (1985)
Goldwasser, S., Micali, S., Rackoff, C.: The knowledge complexity of interactive proof systems. SIAM J. Comput. 18(1), 186–208 (1989). https://doi.org/10.1137/0218012
Lee, E.A., Seshia, S.A.: Introduction to Embedded Systems - A Cyber-Physical Systems Approach, Second edn. MIT Press, Cambridge (2017). http://LeeSeshia.org
Lee, E.A.: Living Digital Beings – A New Life Form on Our Planet? MIT Press, Cambridge (2020, to appear)
Milner, R.: Communication and Concurrency. Prentice Hall, Englewood Cliffs (1989)
Milner, R.: Elements of interaction. Commun. ACM 36, 78–89 (1993)
Park, D.: Concurrency and automata on infinite sequences. In: Deussen, P. (ed.) GI-TCS 1981. LNCS, vol. 104, pp. 167–183. Springer, Heidelberg (1981). https://doi.org/10.1007/BFb0017309
Pearl, J.: Causality: Models, Reasoning, and Inference, 2nd edn. Cambridge University Press, Cambridge (2000). (2009)
Pearl, J., Mackenzie, D.: The Book of Why: The New Science of Cause and Effect. Basic Books, New York (2018)
Quisquater, J.-J., et al.: How to explain zero-knowledge protocols to your children. In: Brassard, G. (ed.) CRYPTO 1989. LNCS, vol. 435, pp. 628–631. Springer, New York (1990). https://doi.org/10.1007/0-387-34805-0_60
Sangiorgi, D.: On the origins of bisimulation and coinduction. ACM Trans. Program. Lang. Syst. 31(4), 15:1–15:41 (2009). https://doi.org/10.1145/1516507.1516510. Article 15, Pub. date: May 2009
Talcott, C.L.: Interaction semantics for components of distributed systems. In: Najm, E., Stefani, J.B. (eds.) Formal Methods for Open Object-Based Distributed Systems (FMOODS). IFIPAICT, pp. 154–169. Springer, Heidelberg (1996). https://doi.org/10.1007/978-0-387-35082-0_11
Thelen, E.: Grounded in the world: developmental origins of the embodied mind. Infancy 1(1), 3–28 (2000)
Wegner, P.: Why interaction is more powerful than algorithms. Commun. ACM 40(5), 80–91 (1997). https://doi.org/10.1145/253769.253801
Wiener, N.: Cybernetics: Or Control and Communication in the Animal and the Machine. Librairie Hermann & Cie, Paris, and MIT Press, Cambridge (1948)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Lee, E.A. (2019). Observation and Interaction. In: Martín-Vide, C., Okhotin, A., Shapira, D. (eds) Language and Automata Theory and Applications. LATA 2019. Lecture Notes in Computer Science(), vol 11417. Springer, Cham. https://doi.org/10.1007/978-3-030-13435-8_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-13435-8_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-13434-1
Online ISBN: 978-3-030-13435-8
eBook Packages: Computer ScienceComputer Science (R0)