# A Revised Attack on Computational Ontology

## Abstract

There has been an ongoing conflict regarding whether reality is fundamentally digital or analogue. Recently, Floridi has argued that this dichotomy is misapplied. For any attempt to analyse noumenal reality independently of any level of abstraction at which the analysis is conducted is mistaken. In the *pars destruens* of this paper, we argue that Floridi does not establish that it is only levels of abstraction that are analogue or digital, rather than noumenal reality. In the *pars construens* of this paper, we reject a classification of noumenal reality as a deterministic discrete computational system. We show, based on considerations from classical physics, why a deterministic computational view of the universe faces problems (e.g., a reversible computational universe cannot be strictly deterministic).

## Keywords

Digital Digital ontology Discrete Digital computation Reversible computation Levels of abstraction Deterministic Entropy## References

- Adriaans, P., & Van Emde Boas, P. (2011). Computation, information, and the arrow of time. In S. B. Cooper & A. Sorbi (Eds.),
*Computability in context*(pp. 1–17). World Scientific: Imperial College Press. Google Scholar - Bais, F. A., & Farmer, J. D. (2008). The physics of information. In P. Adriaans & J. van Benthem (Eds.),
*Handbook of the philosophy of information*(pp. 609–683). Amsterdam: Elsevier.CrossRefGoogle Scholar - Baker, H. (1992). NREVERSAL of fortune—The thermodynamics of garbage collection. In Y. Bekkers & J. Cohen (Eds.),
*Memory management*(Vol. 637, pp. 507–524). Berlin, Heidelberg: Springer.CrossRefGoogle Scholar - Bennett, C. H. (1973). Logical reversibility of computation.
*IBM Journal of Research and Development,**17*(6), 525–532.CrossRefzbMATHGoogle Scholar - Blachowicz, J. (1997). Analog representation beyond mental imagery.
*The Journal of Philosophy,**94*(2), 55–84.CrossRefGoogle Scholar - Calude, C. S. (2009). Information: The algorithmic paradigm. In G. Sommaruga (Ed.),
*Formal theories of information*(Vol. 5363, pp. 79–94). Berlin, Heidelberg: Springer-Verlag.CrossRefGoogle Scholar - Calude, C., Campbell, D. I., Svozil, K., & Ştefuanecu, D. (1995). Strong determinism vs. computability. In W. D. Schimanovich, E. Köhler, & P. Stadler (Eds.),
*The foundational debate, complexity and constructivity in mathematics and physics*. Berlin: Springer.Google Scholar - Copeland, B. J. (2002). Accelerating turing machines.
*Minds and Machines,**12*(2), 281–300.CrossRefzbMATHMathSciNetGoogle Scholar - Davies, E. B. (2001). Building infinite machines.
*The British Journal for the Philosophy of Science,**52*(4), 671–682. doi: 10.1093/bjps/52.4.671.CrossRefzbMATHMathSciNetGoogle Scholar - Evans, D. J., & Searles, D. J. (2002). The fluctuation theorem.
*Advances in Physics,**51*(7), 1529–1585.CrossRefGoogle Scholar - Floridi, L. (2009). Against digital ontology.
*Synthese,**168*(1), 151–178.CrossRefzbMATHGoogle Scholar - Floridi, L. (2011).
*The philosophy of information*. Oxford: Oxford University Press.CrossRefGoogle Scholar - Fredkin, E. (1990). An informational process based on reversible universal cellular automata.
*Physica D: Nonlinear Phenomena, 45*(1–3), 254–270.Google Scholar - Fredkin, E. (1992). Finite nature. In G. Chardin (Ed.),
*Proceedings of the XXVIIth Rencontre De Moriond Series*. France: Editions Frontieres.Google Scholar - Fredkin, E., & Toffoli, T. (1982). Conservative logic.
*International Journal of Theoretical Physics, 21*(3–4), 219–253.Google Scholar - Fresco, N. (2010). Explaining computation without semantics: keeping it simple.
*Minds and Machines,**20*(2), 165–181.CrossRefGoogle Scholar - Fresco, N., Primiero, G (2013). Miscomputation.
*Philosophy & Technology, 26*(3), 253–272.Google Scholar - Jaynes, E. T. (1965). Gibbs vs Boltzmann entropies.
*American Journal of Physics,**33*(5), 391–398.CrossRefzbMATHGoogle Scholar - Kant, I. (1996).
*Critique of pure reason*. (W. S. Pluhar, Trans.). Indianapolis, IN: Hackett Pub. Co.Google Scholar - Koupelis, T. (2011).
*In quest of the universe*. Sudbury, MA: Jones and Bartlett Publishers.Google Scholar - Landauer, R. (1961). Irreversibility and heat generation in the computing process.
*IBM Journal of Research and Development,**5*(3), 183–191.CrossRefzbMATHMathSciNetGoogle Scholar - Lange, K.-J., McKenzie, P., & Tapp, A. (2000). Reversible space equals deterministic space.
*Journal of Computer and System Sciences,**60*(2), 354–367.CrossRefzbMATHMathSciNetGoogle Scholar - Laraudogoitia, J. P. (2011). Supertasks. In E. N. Zalta (Ed.),
*The Stanford Encyclopedia of Philosophy (Spring 2011)*. Retrieved from http://plato.stanford.edu/archives/spr2011/entries/spacetime-supertasks/. - Li, M., & Vitányi, P. M. B. (2008).
*An introduction to Kolmogorov complexity and its applications*. New York: Springer.CrossRefzbMATHGoogle Scholar - Maley, C. J. (2010). Analog and digital, continuous and discrete.
*Philosophical Studies,**155*(1), 117–131.CrossRefGoogle Scholar - Maroney, O. J. E. (2009). Does a computer have an arrow of time?
*Foundations of Physics, 40*(2), 205–238.Google Scholar - Modgil, M. S. (2009). Loschmidt’s paradox, entropy and the topology of spacetime.
*arxiv*:*0907.3165*.Google Scholar - O’Brien, G., & Opie, J. (2006). How do connectionist networks compute?
*Cognitive Processing,**7*(1), 30–41.CrossRefGoogle Scholar - Piccinini, G. (2007). Computation without representation.
*Philosophical Studies,**137*(2), 205–241.CrossRefMathSciNetGoogle Scholar - Popper, K. R. (1950a). Indeterminism in quantum physics and in classical physics. Part I.
*British Journal for the Philosophy of Science,**1*(2), 117–133.CrossRefzbMATHMathSciNetGoogle Scholar - Popper, K. R. (1950b). Indeterminism in quantum physics and in classical physics. Part II.
*British Journal for the Philosophy of Science,**1*(3), 173–195.CrossRefMathSciNetGoogle Scholar - Pylyshyn, Z. W. (1984).
*Computation and cognition: Toward a foundation for cognitive science*. Cambridge, MA: The MIT Press.Google Scholar - Rapaport, W. J. (1998). How minds can be computational systems.
*Journal of Experimental & Theoretical Artificial Intelligence,**10*(4), 403–419.CrossRefzbMATHGoogle Scholar - Schulman, L. S. (2005). A Computer’s arrow of time.
*Entropy,**7*(4), 221–233.CrossRefzbMATHMathSciNetGoogle Scholar - Steinhart, E. (1998). Digital metaphysics. In T. W. Bynum & J. H. Moor (Eds.),
*The digital phoenix*(pp. 117–134). Cambridge: Blackwell. Google Scholar - Strawson, G. (2008). Can we know the nature of reality as it is in itself? In G. Strawson (Ed.),
*Real materialism: And other essays*(pp. 75–100). Oxford: Oxford University Press.Google Scholar - Sutner, K. (2004). The complexity of reversible cellular automata.
*Theoretical Computer Science,**325*(2), 317–328.CrossRefzbMATHMathSciNetGoogle Scholar - Teixeira, A., Matos, A., Souto, A., & Antunes, L. (2011). Entropy measures vs. kolmogorov complexity.
*Entropy,**13*(12), 595–611.CrossRefzbMATHMathSciNetGoogle Scholar - Vitányi, P. (2005). Time, space, and energy in reversible computing. In
*Proceedings of the 2nd conference on computing frontiers*(pp. 435–444). ACM: ACM Press.Google Scholar - Wheeler, J. (1982). The computer and the universe.
*International Journal of Theoretical Physics,**21*(6–7), 557–572.CrossRefGoogle Scholar - Wolfram, S. (2002).
*A new kind of science*. Champaign, IL: Wolfram Media.Google Scholar - Wolpert, D. H. (2001). Computational capabilities of physical systems.
*Physical Review E,**65*(1), 016128.CrossRefMathSciNetGoogle Scholar - Zuse, K. (1970).
*Calculating space*. Cambridge, MA: Massachusetts Institute of Technology, Project MAC.Google Scholar - Zuse, Konrad. (1993).
*The computer—My life*. Berlin: Springer-Verlag.zbMATHGoogle Scholar