School of Computer Science THE UNIVERSITY OF BIRMINGHAM Ghost Machine

Invited talk for symposium on emotions AISB 2017

Architectures underlying cognition and affect in natural and artificial systems

Aaron Sloman
School of Computer Science, University of Birmingham, UK


A deep understanding of human (or animal) minds requires a broad and deep understanding of the types of information processing functions and information processing mechanisms produced by biological evolution, and how those functions and mechanisms are combined in architectures of increasing sophistication and complexity over evolutionary trajectories leading to new species, and how various kinds of evolved potential are realised by context-sensitive mechanisms during individual development. Some aspects of individual development add context-specific detail to products of the evolutionary history, partly because evolution cannot produce pre-packaged specifications for complete information processing architectures, except for the very simplest organisms. Instead, for more complex organisms, including humans, different architectural layers develop at different times during an individual's life, partly under the influence of the genome and partly under the influence of what the individual has so far experienced, learnt, and developed. This is particularly obvious in language development in humans, but that is a special case of a general biological pattern (identified in joint work with Jackie Chappell, partly inspired by theories of Annette Karmiloff-Smith, among others). This paper complements a paper presented in the Symposium on Computing and Philosophy at AISB 2017, which develops more general ideas about evolution of information processing functions and mechanisms, partly inspired by Turing's work on morphogenesis:


Biological organisms differ in many ways. Members of the same species
can differ according to their stage of development, according to the
problems and resources (including information) encountered during their
development, according to details of their genome, and details of
previous development, growth, and learning opportunities and also in
details of their particular environments with different threats,
opportunities, resources, obstacles, competitors, helpers, current
needs, and so on.

Variations across species are even greater. Over billions of years,
biological evolution on this planet has produced a staggering variety of
forms of life, differing in physical size, change of size during the
life of individuals, life span, sensory apparatus, modes of development
and motion, types of environment, modes of interaction with the
environment including conspecifics and other life forms, food, prey,
predators, forms of information storage, modes of reproduction, and many
more. All of these differences (most of which are structural not
numerical) can affect mechanisms, internal states or processes, and
externally visible forms of behaviour or expression, including affective
states and processes related to motivation, goals, plans, preferences,
desires, attitudes, values, hopes, ambitions, decisions, intentions,
concerns, moods, and other affective states and processes.

Is this an area that is susceptible of scientific study and accurate
modelling, or is there merely a hopelessly unstructured mess/tangle of
special cases understood in depth by some novelists, poets, playwrights
counsellors and therapists, but unfit to be the subject of scientific

A similar question might have been asked about chemistry centuries ago
when alchemists were faced with a tangled mess of special cases with no
means of expanding knowledge except by doing more experiments. But that
situation was changed by discoveries about the atomic structure of
matter, including the details summarised in the periodic table of the
elements, along with advances in chemical understanding based on many
experiments and applications of new ideas from quantum mechanics -
producing explanations that were not possible  in the framework of
Newtonian mechanics. Chemical reactions could not be explained by
Newton's laws of motion, but new explanatory theories emerged from
information about the structure of atoms related to the facts assembled
in the periodic table of physical elements, later elaborated by
developments in quantum physics able to explain chemical structures and
mechanisms including some that are crucial for biological evolution
analysed in 1944 by Schrödinger.

Since then, although huge gaps remain in our biological knowledge, there
have been tremendous advances based on theories in physics and chemistry
about possible structures and their interactions, often forming new
structures essential to processes of biological reproduction, growth and

In contrast, much (so-called) scientific study of minds has relied on
correlation-seeking experiments and the use of independently variable
components of vectors to describe complexity - which would be hopelessly
inadequate even for the study of complex molecules.

There is also a wide-spread assumption that all motivation needs to be
thought of in terms of the relative attractions (or repulsions) of
various kinds of reward (or punishment) with a common (positive or
negative) utility measure. This can be compared with the ancient
assumption that all physical masses seek the centre of the universe,
which is hopelessly inadequate for the explanation of known physical and
chemical phenomena.

Even if there are reward mechanisms that explain some motives and
preferences, there is much they cannot explain. For example, if someone
really enjoys doing mathematical research only because doing it produces
some reward (whether chemical or psychological) then in principle he or
she should be just as willing to get the reward by doing something much
easier than struggling with mathematical problems - e.g. drinking some
potion, or stepping into an otherwise harmless machine. But nobody who
really enjoys doing mathematics would swap the activity for one
of its side-effects. Of course, there may be such people for whom doing
mathematics is not its own reward, but they still want to do it, e.g.
because they enjoy the admiration it produces in others, or because it
is a necessary condition for achieving some other goal, such as getting
into university, or a useful aid to attracting an intelligent mate.

I believe I first encountered that refutation of popular reward-based
theories of motivation in Ryle[1949]. There are similar objections to
widely used utility-based mathematical theories of decision making, such
as theories based on "payoff matrices" (criticised in my 1978 book).

I suggest that evolution frequently made use of architecture-based
motive-generation mechanisms (ABM) that, unlike reward-based
motivation (RBM) allow new motives to be triggered by perceived
opportunities or situations without the individual having any ulterior
reward-motive. It suffices that ancestors who had such mechanisms
acquired useful knowledge that later brought benefits that the
individuals could not have predicted, or even thought about. As a result
they succeeded in life and produced offspring who were likely to share
the same motive-generators. So the ABM mechanisms trigger motives that
have been beneficial in one's ancestors, not motives whose achievements
produce some special reward-juice. These can be thought of as
genetically programmed internal reflexes comparable to genetically
programmed physical protective and feeding reflexes.


Across all the variation in forms of life, are there any common
principles? One seems to be the ability to acquire and use information
for purposes of control, such as generating options for consideration,
selecting options, working out consequences of various options. There is
also information-based control of chemical and physical processes of
reproduction, development and growth.

Information is used during interaction with inert physical features of
the environment and also during interaction with predators, prey,
offspring and other conspecifics - which often requires information
about information, e.g. using information about what something else
wants or can perceive.

In many cases passive individuals are acted on by the environment, for
instance when seeds are dispersed by wind, or when seasonal or daily
changes in temperature or availability of light, air or water currents,
or supply of nutrients or dangers are out of the control of individuals
and they can at most resist, react to avoid or react to make use of
(e.g. consume) contents of their environment.

In more complex cases information about threats, opportunities,
resources, and obstacles can be acquired and put to use, either
immediately or at a later time when a need arises. Coping with threats
from other organisms, may involve purely physical avoidance or escape
actions. But in some cases it requires other-directed meta-cognition:
inferring intentions, knowledge, reasoning processes and choosing means
of avoidance or escape accordingly.

So information of many kinds plays many different roles in living
things, unlike non living but interacting physical objects and
processes, such as weather features, geological features shaped by and
shaping one another, including tectonic motion, earthquakes, volcanoes,
floods, tornadoes, other weather patterns, seasonal changes caused by
motion around the sun and tides caused by rotation of the moon around
the earth.

This notion of information is much older than the notion developed by
Shannon around 1948. Since Shannon, information is often discussed as if
it were primarily the content of messages, with senders and receivers.
But sending and receiving messages would be pointless if the message
contents had no other use than to be transmitted, received, encoded,
decoded, compressed, decompressed, stored, retrieved, etc.

The fundamental fact about information that is often ignored in
discussions of the nature of information is that it can be used in
CONTROLLING what happens.

This can take many forms: in some cases information directly triggers a
response, e.g. a defensive reflex such as blinking or rapid withdrawal,
or an opportunity taken, such as motion towards water, food, shelter or
a mate, or use of a body part to acquire or consume something edible.
In other cases the information can be stored for future use, e.g.
information about where a resource or a danger is located, or
information encoded in a genome that is used at a particular stage
during during reproductive processes to control aspects of development
and growth of tissues and parts of new individuals. Other forms of
information in a genome can generate and control behaviours of organisms
once they are functional, e.g. controlling breathing, pumping of blood,
digestion, begging for food, following parents, and triggering new
motives to be acted on later (ABM).

Such uses of information could be ignored in Shannon's famous
work on information [1948] because he was working for a company (Bell
Telephone Company) providing information services, for whom the main
problems were reliable transmission and storage, not use of information.
The USE was the concern of their customers.

In contrast, the novelist Jane Austen was very much concerned with ways
in which her characters could not only transmit, acquire and store
information, but also use it, as discussed in

She frequently referred to information, not in Shannon's sense, but in
the much older sense in which information is used, not merely
transmitted or stored.


There are two fundamentally different roles that useful information can
have, as Hume noted in distinguishing "is" (information about what is
the case) from "ought" (information about what to do) in his argument
that "ought" can never be derived from "is". This distinction was
elaborated by Elizabeth Anscombe [1957] as a difference in "direction of

For an information user there are some information contents (which we
can crudely label "desire-like information") whose role in an organism
determines what should be done to the world to make the world match the
information content, and other information contents (which we can
crudely label "belief-like information") whose role is such that the
information should be altered when there is a mismatch with how the
world is. Both sorts are required for intelligent, or purposeful action,
or deliberate inaction.

Moreover, in both cases there is always the possibility of an organism
not being in a position to determine whether the information item does
or does not match reality - e.g. whether some belief is true, or whether
some desire or goal has been satisfied. This can generate a new
second order desire-like information state, which specifies
that an information gap needs to be bridged. That new state can trigger
action to fill the information gap - which may either be done relatively
simply (e.g. by looking, sniffing, touching, etc.) or by engaging in
some sort of information-gathering research, e.g. to find out whether
food is available nearby and if so where it is.

As these examples show, there can be many processes by which
combinations of belief-like and desire-like information states can
generate actions to determine whether the belief-like states actually
fit the world or actions to make the world fit the desire-like states. A
rich theory of varieties of cognition and affect can be based on the
implications of this distinction as pointed out (by Sloman, Chrisley and
Scheutz) in [2005] (building on ideas developed by Beaudoin[1994]).

The time scales involved and the scale of action required to bridge
these information gaps (finding out whether X is true, or making X true)
can vary enormously according to the complexity of the information
specification and the amount of effort involved in checking whether X
fits the facts or making X fit the facts.

Things get even more complex if individuals can have a large and
changing collection of desire-like and belief-like information states,
unlike a simple thermostat which has a target temperature and a sensor
providing information about the gap between the current and target
states, along with a mechanism for turning on or turning off a heat
generator or heat remover. It is often assumed that all desire-like
information states are concerned with achievement or maximisation of
some measurable reward or utility, but life is far too complex for that:
organisms have many different needs at different stages of development
and at different times and places, often needs that coexist and
conflict, e.g. a need to approach a source of food when energy stores
are low and a need to avoid detection by a dangerous predator or rival.
The assumption that these needs can be compared on a common scale are as
misguided as the assumption that strength of materials and fuel energy
of materials can be compared on a common scale.
Fig 1: Varieties of developmental trajectory proposed by Chappell & Sloman. Later processes can be triggered by delayed genome products interacting with environmental information acquired at earlier stages. (Chris Miall helped with the original diagram.)
This is very different from a form of learning or development that
uses a uniform method for repeatedly finding patterns at
different levels of abstraction, e.g. using statistical generalisations.

Instead, on this model, the genome encodes increasingly abstract and
powerful creative mechanisms developed at different stages of evolution,
that are "awakened" (a notion also used by Kant[1781]) in individuals
only when their time is ready, so that they can build on what has
already been learned or created in a manner that is tailored to the
current environment.


As living things become more complex, increasingly varied types of
information are required for increasingly varied uses. The processes of
reproduction normally produce new individuals that have seriously
under-developed physical structures and behavioural competences.
Self-development requires physical materials, but it also requires
information about what to do with the materials, including disassembling
and reassembling chemical structures at a microscopic level and using
the products to assemble larger body parts, while constantly providing
new materials, removing waste products and consuming energy. Some energy
is stored and some is used in assembly and other processes.

The earliest organisms can acquire and use information about (i.e.
sense) only internal states and processes and the immediate external
environment, e.g. pressure, temperature, and presence of chemicals in
the surrounding soup, with all uses of information taking the form of
immediate local reactions, e.g. allowing a molecule through a membrane.

Some of the changes in types of information, types of use
of information and types of biological mechanism for processing
information have repeatedly altered the processes of evolutionary
morphogenesis that produce such changes: a positive feedback process. A
familiar example is the influence of mate selection on evolution in
intelligent organisms, since mate selection is itself dependent on
previous evolution of new cognitive mechanisms. This is a process with
multiple feedback loops between new designs and new requirements
(niches), as suggested in [Sloman 2000].
Compare also the author's presentation at the Computing and Philosophy
symposium at AISB 2017.

As Figure 1 suggests, evolution constantly produces new organisms that
may or may not be larger than predecessors, but are more complex both in
the types of physical action they can produce and also the types of
information and types of information-processing required for selection
and control of such actions.

These ideas, and those in [Sloman, (2014--)] suggest that one of the
effects of biological evolution was fairly recent production of
extremely, but not totally, abstract construction kits that come into
play at different stages in development, that produce much more rapid
changes in variety and complexity of information processing across
generations than ever before. This idea is fairly familiar as regards
the role of a common genetic inheritance in enabling hugely varied
languages to be developed by humans in different cultures. This pattern
can be generalised to other aspects of development, as suggested in
Figure 1.

(There are loose connections with Chomsky's ideas on evolution and
development of language. I don't think he ever realised that human
language evolution and development must be a special case of something
deeper and more general.)

The talk will present some ideas about possible information processing
architectures capable of supporting diverse kinds of variety among
humans and other animals. I suggest that within a century or two our
ideas about how human minds work, and the requirements for modelling
them in intelligent machines, will have changed at least as much as our
ideas about physics and chemistry have changed since the time of
Galileo. Some suggestions, regarding mechanisms and architectures can be
found in references.


G.E.M. Anscombe, Intention, Blackwell, 1957.
L.P. Beaudoin, Goal processing in autonomous agents, PhD Thesis School of Computer Science, University of Birmingham, 1994, Birmingham, UK;
Jackie Chappell and Aaron Sloman, `Natural and artificial meta-configured altricial information-processing systems', International Journal of Unconventional Computing, 3(3), 211-239, (2007).
I. Kant, Critique of Pure Reason, Macmillan, London, 1781. Translated (1929) by Norman Kemp Smith.
A Karmiloff-Smith, Beyond Modularity: A Developmental Perspective on Cognitive Science, MIT Press, Cambridge, MA, 1992.
G. Ryle, The Concept of Mind, Hutchinson, London, 1949.
Erwin Schrödinger, What is life?, CUP, Cambridge, 1944.
Ann Senghas, `Language Emergence: Clues from a New Bedouin Sign Language', Current Biology, 15(12), R463-R465, (2005).
Claude Shannon, `A mathematical theory of communication', Bell System Technical Journal, 27, 379-423 and 623-656, (July and October 1948).
A. Sloman, The computer revolution in philosophy: Philosophy, science and models of mind Harvester Press and Humanities Press, 1978. Revised online edition (2001-2017):
A. Sloman, `Interacting trajectories in design space and niche space: A philosopher speculates about evolution', in Parallel Problem Solving from Nature - PPSN VI, ed., et al. M.Schoenauer, Lecture Notes in Computer Science, No 1917, pp. 3-16, Berlin, (2000). Springer-Verlag.,
A. Sloman, `The Cognition and Affect Project: Architectures, Architecture-Schemas, And The New Science of Mind', Technical report, School of Computer Science, University of Birmingham, Birmingham, UK, (2003). (Revised August 2008).
A. Sloman, R.L. Chrisley, and M. Scheutz, `The architectural basis of affective states and processes', in Who Needs Emotions?: The Brain Meets the Robot, eds., M. Arbib and J-M. Fellous, 203-244, Oxford University Press, New York, (2005).\#200305.
A. Sloman, `Architecture-Based Motivation vs Reward-Based Motivation', in Newsletter on Philosophy and Computers, 09, 1, pp. 10-13, Newark, (2009), American Philosophical Association.
A. Sloman, `Virtual Machine Functionalism (The only form of functionalism worth taking seriously in Philosophy of Mind and theories of Consciousness)', Research note, School of Computer Science, The University of Birmingham, (2013).

Aaron Sloman, (2014--) Construction Kits for Evolving life


(This is an expanded version of the summary in the Symposium proceedings)

2 Some annotated extracts are available here 3