MIND AS A LAYERED NETWORK OF COMPUTATIONAL
PROCESSES ALL THE WAY DOWN TO QUANTUM
Abstract. Talking about models of cognition, the very mention of “computationalism” often incites reactions
against Turing machine model of the brain and perceived determinism of computational models of mind. Neither
of those two objections affects models based on natural computation or computing nature where model of
computation is broader than deterministic symbol manipulation of conventional models of computation.
Computing nature consists of physical structures that form levels of organization, on which computation
processes differ, from quantum level up. It has been argued by (Ehresmann, 2012) and (Ghosh et al., 2014) that
on the lower levels of information processing in the brain finite automata or Turing machines might be adequate
models, while on the level of the whole-brain information processing computational models beyond-Turing
computation is necessary.
Critique of Computationalism Answered by New Understanding of Computation
Historically, computationalism has been accused of many sins (Miłkowski, 2013) (Scheutz, 2002). In what follows
I would like to answer Mark Sprevak’s three concerns about computationalism, (Sprevak, 2012) p. 108:
(R1) Lack of Clarity: “Ultimately, the foundations of our sciences should be clear.” Computationalism is suspected
to lack clarity.
(R2) Triviality: “(O)ur conventional understanding of the notion of computational implementation is threatened
by triviality arguments.” Computationalism is accused of triviality.
(R3) Lack of naturalistic foundations: “The ultimate aim of cognitive science is to offer, not just any explanation
of mental phenomena, but a naturalistic explanation of the mind.” Computationalism is questioned for being
formal and unnatural.
Sprevak concludes that meeting all three above expectations of computational implementation is hard. As an
illustration he presents David Chalmers computational formalism of combinatorial state automata and concludes
that “Chalmers’ account provides the best attempt to do so, but even his proposal falls short.” In order to be fully
understood, Chalmers account, I will argue, should be seen from the perspective of intrinsic, natural computation
instead of conventional designed computer. Chalmers argues:
“Computational descriptions of physical systems need not be vacuous. We have seen that there is a wellmotivated formalism, that of combinatorial state automata, and an associated account of implementation, such
that the automata in question are implemented approximately when we would expect them to be: when the
causal organization of a physical system mirrors the formal organization of an automaton. In this way, we
establish a bridge between the formal automata of computation theory and the physical systems of everyday life.
We also open the way to a computational foundation for the theory of mind.” (Chalmers, 1996)
In the above it is important to highlight the distinction between intrinsic /natural/ spontaneous computation that
describes natural processes at different levels of organization and is always present in physical system and
designed/conventional computation which is used in our technological devices and which uses intrinsic
computation as its basis.
Already in 2002 Matthias Scheutz (Scheutz, 2002) had a proposal for new computationalism capable of
accounting for embodiment and embeddedness of mind. In this article we will present the recent developments
that show how this new computationalism looks like and in what directions it is developing.
Natural/Intrinsic Computation and Physical Implementation of Computational
System
The way to avoid the criticisms against computational models of mind is to naturalize computation.
The idea of computing nature (Dodig-Crnkovic & Giovagnoli, 2013) (Zenil, 2012) builds on the notion of physical
computation, described in (Piccinini, 2012) also termed “computation in materio” by Stepney (Stepney, 2008,
2012) that is the idea that the universe as a whole can be seen as a computational system which computes its
own next state. This approach is called pancomputationalism or natural computationalism and dates back to
Konrad Zuse, with many prominent representatives such as Edward Fredkin, Stephen Wolfram and Greg Chaitin
among others. (a few words on physical computation here). [Here introduce info-computationalism Floridi Burgin
Marcin] In the framework of info-computationalism, which is a variety of pancomputationalism, physical nature
spontaneously performs different kinds of computations that present information dynamics at different levels of
organization (Dodig-Crnkovic, 2012). This intrinsic computation of a physical system can be used for designed
computation, which would not appear spontaneously in nature, but with constant energy supply and designed
architecture performs computations such as found in conventional designed computational machinery.
It should be noted that varieties of natural computationalism/ pancomputationalism differ among themselves:
some of them would insist on discreteness of computation, and the idea that on the deepest levels of
description, nature should be seen as discrete. Others find the origin of the continuous/discrete distinction in the
human cognitive apparatus that relies on both continuous and discrete information processing (computation),
thus arguing that both discrete and continuous and discrete models are necessary (Dodig-Crnkovic & Mueller,
2009) (Lloyd, 2006).
Why is natural computationalism not vacuous in spite of the underlying assumption of the whole of the universe
being computational? It is not vacuous for the same reason for which physics is not vacuous even though it
makes the claim that the entire physical universe consists of matter-energy and builds on the same elementary
building blocks – elementary particles. *(Here we will not enter the discussion of ordinary matter-energy vs. dark
matter-energy. Those are all considered to be the same kind of phenomena – natural phenomena that are
assumed to be universal in nature.) The principle of universal validity of physical laws does not make them
vacuous. Thinking of computation as implementation of physical laws on the fundamental level makes it more
obvious that computation can be seen as the basis of all dynamics in nature.
Introduction to Focus Issue: Intrinsic and Designed Computation:
Information Processing in Dynamical Systems—
Beyond the Digital Hegemony
James P. Crutchfield,1,a! William L. Ditto,2,b! and Sudeshna Sinha3,c!
Thinking of intrinsic computation on the most fundamental level of natural process “in materio” (Stepney, 2008).
Causation is transfer of information (Collier, 1999) and computation, as information processing, is causation at
work, as argued in (Dodig-Crnkovic, …). What are the implications of this view for computing nature in general
and computational models of mind in particlular?
Top-Down Causation
Walker Sara Imari. Top-Down Causation and the Rise of Information in the Emergence of Life. Information. 2014;
5(3):424-439. (Walker, 2014)
CARL F. CRAVER, and WILLIAM BECHTEL, Top-down causation without top-down causes, Biology and Philosophy
(2006) (Craver & Bechtel, 2007)
In his Open Problems in the Philosophy of Information (Floridi, 2004) lists the five most interesting areas of
research for the nascent field of Philosophy of Information (and Computation), containing eighteen fundamental
questions as follows:
17. The “It from Bit” hypothesis: Is the universe essentially made of informational stuff, with natural
processes, including causation, as special cases of information dynamics?
KAMPIS: CAUSAL DEPTH
Network of causal connectedness
Andre Ehresmann talks about synonymity
Memory Evolutive Systems (Ehresmann, 2012)(Ehresmann, 2014)
However, Marcin Miłkowski suggests “the physical implementation of a computational system – and its
interaction with the environment – lies outside the scope of computational explanation”.
”For a pancomputationalist, this means that there must be a distinction between lower-level, or basic,
computations and the higher level ones. Should pancomputationalism be unable to mark this distinction, it will be
explanatorily vacuous.” (Miłkowski, 2007)
From the above I infer that the model of computation, which Miłkowski assumes is a top-down, designed
computation. Even though he rightly argues that neural networks and even dynamical systems can be
understood as computational, Miłkowski does not think of intrinsic computation as grounded in physical process
driven by causal mechanism, characteristics of computing nature.
The problem of physical computation is related to the problem of grounding of the concept of computation.
Where the following question comes from?
If we would apply the above logic, we would demand from physicists to explain where matter comes from.
Where do the elementary particles come from? They are simply empirical facts for which we have enough
evidence. We might not know all of their properties and relationships, we might not know all of them, but we can
be sure at least that they exist. The bottom layer for the computational universe is the bottom layer of its
material substrate, which with constant progress of physics is becoming more and more fine-grained.
Levels of Organization and Agent-based Model of Computation
Mind as a Process and Computational Models of Mind
Of all computational approaches, the most controversial are the computational models of mind. There exists
historically a huge variety of models, some of them taking mind to be a kind of immaterial substance opposed to
material body, the most famous being Platonic and Cartesian dualist models. Through hylomorphism, in contrast
to reductive materialism, which identifies body and mind, and Platonic dualism, which takes body and mind to be
separate substances, Aristotle proposes a unifying approach where mind represents the form of a material body.
It is more natural for computational approaches to consider mind as a process of changing form, a complex
process of computation on many different levels of organization of matter.
“To sum up: mind is a set of processes distinguished from others through their control by an immanent end. (…)
At one extreme it dwindles into mere life, which is incipient mind. At the other extreme it vanishes in the clouds; it
does not yet appear what we shall be. Mind as it exists in ourselves is on an intermediate level.” (Blanshard, 1941)
Within info-computational framework, cognition is understood as synonymous with process of life, a view that
even Brand Blanshard adopted. Following Maturana and Varela’s argument from 1980 (Maturana & Varela,
1980), we can understand the entire living word as possessing cognition of various degrees of complexity. In that
sense bacteria possess rudimentary cognition expressed in quorum sensing and other collective phenomena
based on information communication and information processing. Brain of a complex organism consists of
neurons that are networked communication computational units. Signalling and information processing modes
of a brain are much more complex and consist of more computational layers than bacterial colony. Even though
Maturana and Varela did not think of cognition as computation, the broader view of computation as found in
info-computationalism is capable of representing processes of life as studied in bioinformatics and
biocomputation.
Relation between mind and cognition [Marcin’s book]
http://www.scholarpedia.org/article/Mind-body_problem:_New_approaches
Starting with mind as life itself, a single cell, and studying increasingly more complex organisms such as rotifers
(which have around a thousand cells, of which a quarter constitute their nervous system with brain) or the tiny
Megaphragma mymaripenne wasps (that are smaller than a single-celled amoebas and yet have nervous system
and brains) – with more and more layers of cognitive information-processing architectures we can follow the
evolution of mind as a capacity of a living organism to act on their own behalf:
“(W)herever mind is present, there the pursuit of ends is present”. (…) ”Mental activity is the sort of activity
everywhere whose reach exceeds its grasp.” (…) “Now mind, at all of its levels and in all of its manifestations, is a
process of this kind” [i.e. a drive toward a special end]. (Blanshard, 1941)
And the process powering this goal-directed behavior on a variety of levels of organization in living organisms is
information self-organization. Andre Ehresmann (Ehresmann, 2012) proposes the model of brain where lower
levels are made of Turing machines while the higher levels of cognitive activity are non-Turing, based on the fact
that the same symbol has several possible interpretations. In contrast, Subrata Ghosh et al. (Ghosh et al., 2014)
remarkable brain model demonstrates how mind can be modelled from the level of quantum field theory up to
the macroscopic whole-brain, in twelve levels of computational architecture, based on computing beyond Turing
model.
REFERENCES
Blanshard, B. (1941). The Nature of Mind. The Journal of Philosophy, 38(8), 207–216.
Chalmers, D. J. (1996). Does a Rock Implement Every Finite-State Automaton? Synthese, 108, 309–33.
Collier, J. (1999). Causation is the transfer of information. In H. Sankey (Ed.), Causation, natural laws and
explanation (pp. 279–331). Dordrecht: Kluwer.
Craver, C., & Bechtel, W. (2007). Top-down causation without top-down causes. Biology and Philosophy, 22(4),
547–563.
Dodig-Crnkovic, G. (2012). Physical Computation as Dynamics of Form that Glues Everything Together.
Information, 3(2), 204–218.
Dodig-Crnkovic, G., & Giovagnoli, R. (2013). Computing Nature. Berlin Heidelberg: Springer.
Dodig-Crnkovic, G., & Mueller, V. (2009). A Dialogue Concerning Two World Systems: Info-Computational vs.
Mechanistic. (G. Dodig Crnkovic & M. Burgin, Eds.)Information and Computation (pp. 149–84). Singapore:
World Scientific Pub Co Inc.
Ehresmann, A. C. (2012). MENS, an Info-Computational Model for (Neuro-)cognitive Systems Capable of
Creativity. Entropy, 14, 1703–1716.
Ehresmann, A. C. (2014). A Mathematical Model for Info-computationalism. Constructivist Foundations, 9(2),
235–237.
Floridi, L. (2004). Open Problems in the Philosophy of Information. Metaphilosophy, 35(4), 554–582.
Ghosh, S., Aswani, K., Singh, S., Sahu, S., Fujita, D., & Bandyopadhyay, A. (2014). Design and Construction of a
Brain-Like Computer: A New Class of Frequency-Fractal Computing Using Wireless Communication in a
Supramolecular Organic, Inorganic System. Information, 5(1), 28–100. doi:10.3390/info5010028
Lloyd, S. (2006). Programming the universe: a quantum computer scientist takes on the cosmos. New York: Knopf.
Maturana, H., & Varela, F. (1980). Autopoiesis and cognition: the realization of the living. Dordrecht Holland: D.
Reidel Pub. Co.
Miłkowski, M. (2007). Is computationalism trivial? In G. Dodig-Crnkovic & S. Stuart (Eds.), Computation,
Information, Cognition – The Nexus and the Liminal (pp. 236–246). Newcastle UK: Cambridge Scholars
Press.
Miłkowski, M. (2013). Explaining the Computational Mind. Cambridge, Mass.: MIT Press.
Piccinini, G. (2012). Computation in Physical Systems. In The Stanford Encyclopedia of Philosophy.
Scheutz, M. (2002). Computationalism new directions (pp. 1–223). Cambridge Mass.: MIT Press.
Sprevak, M. (2012). Three challenges to Chalmers on computational implementation. Journal of Cognitive
Science, 13(2), 107–143.
Stepney, S. (2008). The neglected pillar of material computation. Physica D: Nonlinear Phenomena, 237(9), 1157–
1164.
Stepney, S. (2012). Programming Unconventional Computers: Dynamics, Development, Self-Reference. Entropy,
14, 1939–1952.
Walker, S. I. (2014). Top-Down Causation and the Rise of Information in the Emergence of Life. Information, 5(3),
424–439.
Zenil, H. (2012). A Computable Universe. Understanding Computation & Exploring Nature As Computation. (H.
Zenil, Ed.). Singapore: World Scientific Publishing Company/Imperial College Press.
From the mail to Terry Deacon
The central claim that I wish to reflect upon is how a system "registers"* information
(and a connected question why it "registers" some information and not the other).
From Deacon’s text (private communication):
"The far-from-equilibrium case is of major importance also because it provides the
foundation for an analysis of the nature of an interpretive process (see next section).
A simple exemplar of a far-from-equilibrium information medium is a metal
detector."
There is for example connection to:
Kaneko, K. and Tsuda, I. "Complex systems: chaos and beyond. A constructive approach with applications in life sciences",
Springer, Berlin/Heidelberg, 2001.
http://books.google.se/books?id=7lcINfgupggC&pg=PA265&dq=Complex+Systems:+C
haos+and+Beyond+by+K.+Kaneko;+I.+Tsuda&hl=en&sa=X&ei=5RVHU8f-E6SbygGmuYGwCA
&ved=0CC0Q6AEwAA#v=onepage&q=Complex%20Systems%3A%20Chaos%20and%20Beyond%20
by%20K.%20Kaneko%3B%20I.%20Tsuda&f=false
They discuss different topics, but this seems to me be of interest in connection to
Deacon’s paper:
Dynamics of living organism creates a sensitive state that reacts on the changes in
the environment.
“Those data are in accordance with the dynamic viewpoint of the brain as proposed
by Tsuda, which can be summarized as follows: a neuron and a neuron assembly are
not structured to reveal a single function, but structured such that they can
implement multiple functions according to the internal states of the brain and the
external environment.
Furthermore, these activities should reveal temporally complex behavior, which
perhaps is related to the chaotic itinerancy. Thus the study of the relational
dynamics among the elements involved in the information processing of the brain
will be an important issue.” P.18
This in turn may be expressed in terms of von Foersters notions of eigenvalues
(stable structures) and eigenbehaviors (stable behaviors established in the
interaction with the environment):
“ Any system, cognitive or biological, which is able to relate internally, selforganized, stable structures (eigenvalues) to constant aspects of its own interaction
with an environment can be said to observe eigenbehavior. Such systems are
defined as organizationally closed because their stable internal states can only be
defined in terms of the overall dynamic structure that supports them.” (Rocha 1998:
342)
Rocha L. M. (1998) Selected self-organization and the semiotics of evolutionary systems. In: Salthe S., Van de Vijver G. & Delpos
M. (eds.) Evolutionary systems: Biological and epistemological perspectives on selection and self-organization. Kluwer,
Dordrecht: p. 342
Similarly, the following thought may be found in Gilbert Simondon's discussion of
form-information relationship:
"The notion of form must be replaced by that of information, which implies the
existence of a system in metastable equilibrium that can individuate; information,
the difference in shape, is never a single term, but the meaning that arises from a
disparation (disappearance)."
Simondon, Gilbert (2007) L'individuation psychique et collective. Paris: Editions Aubier (p. 28, translation by Andrew Iliadis)
In the above picture of a metastable state capable of reacting to the relevant
changes in the environment, two things are particularly interesting (apart from the
meta-stability itself): time-dependence (dynamics) and fractality.
Both are addressed in a radically new approach to the modeling of a whole brain in
the following article by (Ghosh et al., 2014):
Ghosh, Subrata; Aswani, Krishna; Singh, Surabhi; Sahu, Satyajit; Fujita, Daisuke; Bandyopadhyay, Anirban. 2014. "Design and
Construction of a Brain-Like Computer: A New Class of Frequency-Fractal Computing Using Wireless Communication in a
Supramolecular Organic, Inorganic System." Information 5, no. 1: 28-100.
http://www.mdpi.com/2078-2489/5/1/28
What seems interesting in this context is that the central point in the above model is
the collective time behavior and (fractal) frequencies at number of different levels of
organization. (Ghosh et al., 2014) suggest a possibility of connection between levels
from QFT (Quantum Field Theory) up to macroscopic levels based on time
dependence of physical oscillators involved. It might not be an adequate model of a
brain, but as Bohr model of atom it can contain some interesting insights. (refer to
Basti here)
“Here, we introduce a new class of computer which does not use any circuit or logic
gate. In fact, no program needs to be written: it learns by itself and writes its own
program to solve a problem. Gödel's incompleteness argument is explored here to
devise an engine where an astronomically...
Abstract: Here, we introduce a new class of computer which does not
use any circuit or logic gate. In fact, no program needs to be written: it
learns by itself and writes its own program to solve a problem. Gödel’s
incompleteness argument is explored here to devise an engine where
an astronomically large number of “if-then” arguments are allowed to
grow by self-assembly, based on the basic set of arguments written in
the system, thus, we explore the beyond Turing path of computing but
following a fundamentally different route adopted in the last half-a-
century old non-Turing adventures. Our hardware is a multilayered seed
structure. If we open the largest seed, which is the final hardware, we
find several computing seed structures inside, if we take any of them
and open, there are several computing seeds inside. We design and
synthesize the smallest seed, the entire multilayered architecture grows
by itself. The electromagnetic resonance band of each seed looks
similar, but the seeds of any layer shares a common region in its
resonance band with inner and upper layer, hence a chain of resonance
bands is formed (frequency fractal) connecting the smallest to the
largest seed (hence the name invincible rhythm or Ajeya Chhandam in
Sanskrit). The computer solves intractable pattern search (Clique)
problem without searching, since the right pattern written in it
spontaneously replies back to the questioner. To learn, the hardware
filters any kind of sensory input image into several layers of images,
each containing basic geometric polygons (fractal decomposition), and
builds a network among all layers, multi-sensory images are connected
in all possible ways to generate “if” and “then” argument. Several such
arguments and decisions (phase transition from “if” to “then”) selfassemble and form the two giant columns of arguments and rules of
phase transition. Any input question is converted into a pattern as noted
above, and these two astronomically large columns project a solution.
The driving principle of computing is synchronization and desynchronization of network paths, the system drives towards highest
density of coupled arguments for maximum matching. Memory is
located at all layers of the hardware. Learning, computing occurs
everywhere simultaneously. Since resonance chain connects all
computing seeds, wireless processing is feasible without a screening
effect. The computing power is increased by maximizing the density of
resonance states and bandwidth of the resonance chain together. We
discovered this remarkable computing while studying the human brain,
so we present a new model of the human brain in terms of an
experimentally determined resonance chain with bandwidth 10−15 Hz
(complete brain with all sensors) to 10+15 Hz (DNA) along with its
implementation using a pure organic synthesis of entire computer (brain
jelly) in our lab, software prototype as proof of concept and finally a new
fourth circuit element (Hinductor) based beyond Complementary metaloxide semiconductor (CMOS) hardware is also presented.
Keywords: Turing machine; Gödel’s incompleteness theorem; nonalgorithmic computing; self-assembly; wireless communication;
antenna; receiver; electromagnetic resonance; synchronization; brainlike computer; creative machine; intelligent machine; conscious
machine
*This expression I borrow from Brian Cantwell Smith's "On the Origin of
Objects"
Top-down causation without top-down causes
Carl F. Craver & William Bechtel
Biology and Philosophy 22 (4):547-563 (2007)
Abstract
We argue that intelligible appeals to interlevel causes (top-down and bottom-up)
can be understood, without remainder, as appeals to mechanistically mediated
effects. Mechanistically mediated effects are hybrids of causal and constitutive
relations, where the causal relations are exclusively intralevel. The idea of causation
would have to stretch to the breaking point to accommodate interlevel causes. The
notion of a mechanistically mediated effect is preferable because it can do all of the
required work without appealing to mysterious interlevel causes. When interlevel
causes can be translated into mechanistically mediated effects, the posited
relationship is intelligible and should raise no special philosophical objections. When
they cannot, they are suspect.
The software/wetware distinction
Comment on “Toward a computational framework for
cognitive biology: Unifying approaches from cognitive
neuroscience and comparative cognition” by W. Tecumseh
Fitch
DanielDennetta,b
aTufts University, United States1
bSanta Fe Institute, United States2
Received23 May 2014; accepted26 May 2014
Fitch WT. Toward a computational framework for cognitive biology: unifying
approaches from cognitive neuroscience and comparative cogni-tion. Phys Life
Rev 2014. http://dx.doi.org/10.1016/j.plrev.2014.04.005[this issue].
« 3 » An MES gives a constructive model for a self-organized multi-scale cognitive system that is able to interact
with its environment through information processing, such as a living organism or an artificial cognitive system.
Its dynamics is modulated by the interactions of a network of specialized internal agents called co-regulators
(CRs). Each CR operates at its own rhythm to collect and process external and/or internal information related to its
function, and possibly to select appropriate procedures. The co-regulators operate with the help of a central,
flexible memory containing the knowledge of the system, which they contribute to develop and adapt to a
changing environment.
« 4 » In an MES, a central role is played by the following properties of information processing in living systems:
(i) The system not only processes isolated information items, but also takes their interactions into account by
processing information patterns, that is patterns of interconnected information items.
(ii) The MES satisfies a multiplicity principle (MP), asserting that several such information patterns may play the
same functional role once actualized, with the possibility of a switch between them during processing operations.
This principle formalizes the degeneracy property that is ubiquitous in biological systems, as emphasized by
Edelman (1989; Edelman & Gally 2001). It permits Gregory Bateson’s sentence (§21) to be completed into “a
difference that makes a difference, but also may not make a difference.” The MP is at the root of the flexibility and
adaptability of an MES; it will also be responsible for the non-computability of its global dynamics.
« 5 » Once actualized in the MES, an information pattern P will take its own identity as a new component cP of a
higher complexity order, which “binds” the pattern, for instance as a record of P in the memory. The binding
process is modeled by the categorical colimit operation (Kan 1958): cP becomes the colimit of P and also of each
of the other functionally-equivalent information patterns; thus it acts as a multi-facetted component. Such multifacetted components are constructed through successive complexification processes (Ehresmann &
Vanbremeersch 2007). The complexification also constructs the links interconnecting two multi-facetted
components cP and cQ. There are simple links, which bind together a cluster of links between the
Hylomorphism
http://en.wikipedia.org/wiki/Hylomorphism
From Wikipedia, the free encyclopedia
This article is about the concept of hylomorphism in Aristotelian philosophy. For the
concept in computer science, see Hylomorphism (computer science).
Hylomorphism is a philosophical theory developed by Aristotle, which conceives being (ousia) as a
compound of matter and form
Matter and form
Aristotle defines X's matter as "that out of which" X is made.[1] For example, letters are the matter of
syllables.[2] Thus, "matter" is a relative term:[3] an object counts as matter relative to something else.
For example, clay is matter relative to a brick because a brick is made of clay, whereas bricks are
matter relative to a brick house.
Change is analyzed as a material transformation: matter is what undergoes a change of form. [4] For
example, consider a lump of bronze that's shaped into a statue. Bronze is the matter, and this matter
loses one form (that of a lump) and gains a new form (that of a statue). [5][6]
According to Aristotle's theory of perception, we perceive an object by receiving its form with our
sense organs.[7] Thus, forms include complex qualia such as colors, textures, and flavors, not just
shapes.[8]
Substantial form, accidental form, and prime matter
See also: Substantial form
Medieval philosophers who used Aristotelian concepts frequently distinguished between substantial
forms and accidental forms. A substance necessarily possesses at least one substantial form. It may also
possess a variety of accidental forms. For Aristotle, a "substance" (ousia) is an individual thing—for
example, an individual man or an individual horse. [9] The substantial form of substance S consists of
S's essential properties,[10] the properties that S's matter needs in order to be the kind of substance that S
is.[11] In contrast, S's accidental forms are S's non-essential properties,[12] properties that S can lose or
gain without changing into a different kind of substance.[13]
In some cases, a substance's matter will itself be a substance. If substance A is made out of substance
B, then substance B is the matter of substance A. However, what is the matter of a substance that is not
made out of any other substance? According to Aristotelians, such a substance has only "prime matter"
as its matter. Prime matter is matter with no substantial form of its own. [14] Thus, it can change into
various kinds of substances without remaining any kind of substance all the time. [15]
Body–soul hylomorphism
Basic theory
See also: On the Soul
Aristotle applies his theory of hylomorphism to living things. He defines a soul as that which makes a
living thing alive.[16] Life is a property of living things, just as knowledge and health are. [17] Therefore,
a soul is a form—that is, a property or set of properties—belonging to a living thing.[18] Furthermore,
Aristotle says that a soul is related to its body as form to matter. [19]
Hence, Aristotle argues, there is no problem in explaining the unity of body and soul, just as there is no
problem in explaining the unity of wax and its shape. [20] Just as a wax object consists of wax with a
certain shape, so a living organism consists of a body with the property of life, which is its soul. On the
basis of his hylomorphic theory, Aristotle rejects the Pythagorean doctrine of reincarnation, ridiculing
the notion that just any soul could inhabit just any body. [21]
According to Timothy Robinson, it is unclear whether Aristotle identifies the soul with the body's
structure.[22] According to one interpretation of Aristotle, a properly organized body is already alive
simply by virtue of its structure.[23] However, according to another interpretation, the property of life—
that is, the soul—is something in addition to the body's structure. Robinson uses the analogy of a car to
explain this second interpretation. A running car is running not only because of its structure but also
because of the activity in its engine.[24] Likewise, according to this second interpretation, a living body
is alive not only because of its structure but also because of an additional property: the soul is this
additional property, which a properly organized body needs in order to be alive. [25] John Vella uses
Frankenstein's monster to illustrate the second interpretation: [26] the corpse lying on Frankenstein's
table is already a fully organized human body, but it is not yet alive; when Frankenstein activates his
machine, the corpse gains a new property, the property of life, which Aristotle would call the soul.
Living bodies
Some scholars have pointed out a problem facing Aristotle's theory of soul-body hylomorphism.[27]
According to Aristotle, a living thing's matter is its body, which needs a soul in order to be alive.
Similarly, a bronze sphere's matter is bronze, which needs roundness in order to be a sphere. Now,
bronze remains the same bronze after ceasing to be a sphere. Therefore, it seems that a body should
remain the same body after death.[28] However, Aristotle implies that a body is no longer the same body
after death.[29] Moreover, Aristotle says that a body that has lost its soul is no longer potentially
alive.[30] But if a living thing's matter is its body, then that body should be potentially alive by
definition.
One approach to resolving this problem[31] relies on the fact that a living body is constantly losing old
matter and gaining new matter. Your five-year-old body consists of different matter than does your
seventy-year-old body. If your five-year-old body and your seventy-year-old body consist of different
matter, then what makes them the same body? The answer is presumably your soul. Because your fiveyear-old body and your seventy-year-old body share your soul—that is, your life—we can identify
them both as your body. Apart from your soul, we cannot identify what collection of matter is your
body. MEMORY! Therefore, your body is no longer your body after it dies. [NO. ARISTOTLE SAYS
YOUR BODY WITHOUT SOUL IS NOT ALIVE. BY DEFINITION. BECAUSE SOUL MEANS
LIFE.]
Another approach to resolving the problem[32] relies on a distinction between "proximate" and "nonproximate" matter. When Aristotle says that the body is matter for a living thing, he may be using the
word "body" to refer to the matter that makes up the fully organized body, rather than the fully
organized body itself. Unlike the fully organized body, this "body" remains the same thing even after
death. In contrast, when he says that the body is no longer the same body after its death, he is using the
word "body" to refer to the fully organized body, which (according to this interpretation) does not
remain the same thing after death.
Intellect
See also: Nous, Active intellect and Passive intellect
Aristotle says that the intellect (nous), the ability to think, has no bodily organ (in contrast with other
psychological abilities, such as sense-perception and imagination).[33] In fact, he says that it is not
mixed with the body[34] and suggests that it can exist apart from the body.[35] This seems to contradict
Aristotle's claim that the soul is a form or property of the body. To complicate matters further, Aristotle
distinguishes between two kinds of intellect or two parts of the intellect. [36] These two intellectual
powers are traditionally called the "passive intellect" and the "active intellect" or "agent intellect".[37]
Thus, interpreters of Aristotle have faced the problem of explaining how the intellect fits into
Aristotle's hylomorphic theory of the soul.
According to one interpretation, a person's ability to think (unlike his other psychological abilities)
belongs to some incorporeal organ distinct from his body. [38] This would amount to a form of
dualism.[39] However, according to some scholars, it would not be a full-fledged Cartesian dualism.[40]
This interpretation creates what Robert Pasnau has called the "mind-soul problem": if the intellect
belongs to an entity distinct from the body, and the soul is the form of the body, then how is the
intellect part of the soul?[41]
Another interpretation rests on the distinction between the passive intellect and the agent intellect.
According to this interpretation, the passive intellect is a property of the body, while the agent intellect
is a substance distinct from the body.[42][43] Some proponents of this interpretation think that each
person has his own agent intellect, which presumably separates from the body at death. [44][45] Others
interpret the agent intellect as a single divine being, perhaps the Unmoved Mover, Aristotle's
God.[46][47]
A third interpretation[48] relies on the theory that an individual form is capable of having properties of
its own.[49] According to this interpretation, the soul is a property of the body, but the ability to think is
a property of the soul itself, not of the body. If that is the case, then the soul is the body's form and yet
thinking need not involve any bodily organ.[50]
……
Modern physics
The idea of hylomorphism can be said to have been reintroduced to the world when Werner Heisenberg
invented his duplex world of quantum mechanics.[69]
"In the experiments about atomic events we have to do with things and facts, with phenomena that are
just as real as any phenomena in daily life. But atoms and the elementary particles themselves are not
as real; they form a world of potentialities or possibilities rather than one of things or facts ... The
probability wave ... mean[s] tendency for something. It's a quantitative version of the old concept of
potentia from Aristotle's philosophy. It introduces something standing in the middle between the idea
of an event and the actual event, a strange kind of physical reality just in the middle between possibility
and reality."
See also
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Endurantism
Hyle
Hylozoism
Identity and change
Inherence
Materialism
Substance theory

Notes
1. Physics 194b23-24
2. Physics 195a16
3. Physics 194b9
4. Robinson 18-19
5. Physics 195a6-8
6. Metaphysics 1045a26-29
7. On the Soul 424a19
8. On the Soul 418a11–12
9. Categories 2a12-14
10. Cross 34
11. Kenny 24
12. Cross 94
13. Kenny 24
14. Leftow 136-37
15. Kenny 25
16. On the Soul 413a20-21
17. On the Soul 414a3-9
18. On the Soul 412a20, 414a15-18
19. On the Soul 412b5-7, 413a1-3, 414a15-18
20. 412b5-6
21. On the Soul 407b20-24, 414a22-24
22. Robinson 45-47
23. Robinson 46
24. Robinson 46
25. Robinson 47
26. Vella 92
27. Shields, Aristotle 290-93
28. Shields, Aristotle 291
29. On the Soul 412b19-24
30. 412b15
31. Shields, Aristotle 293
32. Shields, "A Fundamental Problem"
33. On the Soul 429a26-27
34. On the Soul 429a24-25
35. On the Soul 413b24-26, 429b6
36. On the Soul 15-25
37. Robinson 50
38. Caston, "Aristotle's Psychology" 337
39. Caston, "Aristotle's Psychology" 337
40. Shields, "Some Recent Approaches" 165
41. Pasnau 160
42. McEvilley 534
43. Vella 110
44. Caston, "Aristotle's Two Intellects" 207
45. Vella 110
46. Caston, "Aristotle's Psychology" 339
47. Caston, "Aristotle's Two Intellects" 199
48. Shields, "Soul as Subject"
49. Shields, "Soul as Subject" 142
50. Shields, "Soul as Subject" 145
51. Kenny 26
52. Cross 70
53. Stump, "Resurrection, Reassembly, and Reconstitution: Aquinas on the Soul"
161
54. Leftow, "Soul, Mind, and Brain" 397
55. Stump, "Resurrection, Reassembly, and Reconstitution: Aquinas on the Soul"
165
56. Eberl 340
57. Eberl 341
58. Stump, "Resurrection, Reassembly, and Reconstitution: Aquinas on the Soul"
161
59. Stump, "Non-Cartesian Substance Dualism and Materialism without
Reductionism" 514
60. Stump,"Non-Cartesian Substance Dualism and Materialism without
Reductionism" 512
61. Stump, "Non-Cartesian Substance Dualism and Materialism without
Reductionism" 512
62. Stump, "Non-Cartesian Substance Dualism and Materialism without
Reductionism" 519
63. Irwin 237
64. Metaphysics 1050a15
65. Irwin 237
66. Nichomachean Ethics 1098a16-18
67. Nichomachean Ethics 1098a1-5
68. Nichomachean Ethics 1098a7-8
69. Herbert, Nick (1985). Quantum Reality: Beyond the New Physics. New York:
Anchor Books. pp. 26–27.
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Nichomachean Ethics
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