Abstracts
MS
no
1
2
3
Author /
Institution
Margret
Bowden
Peter Burton
Honorary
Fellow, ACU
(Canberra)
Title
Abstract
Computational
creativity
Cognitive
Architecture:
Issues of Control
and Effective
Computation
N/A
Nir Fresco
PhD
candidate,
School of
history and
philosophy,
UNSW
(Sydney)
The Information
Processing
Account of
Computation
Biologically inspired cognitive architectures are developing to modularise
and emulate aspects of human cognition, but do not yet seem to be
questioning the implicit presumption of universality in the application or
scope of ‘effective’ (syntactically symbolic) computation in their models of
natural human intelligence. For example, my Cognitive System Theory
requires a 2D ‘balance-board’ steering control for its model of the self, a kind
more ‘intuitive’ than syntactic or ‘rational'. Therefore, the paper will
reconsider all aspects of control within embodied cognitive systems, as this
control relates particularly to issues of autonomy, agency and the control
associated with the self-model. These issues will be considered from multiple
perspectives, ranging from exadaptive control theory as a way of approaching
the emergence of human intelligence, to considering what is yet to be
embodied to reach a hominid quality of (self-aware) intelligence in robotic
systems, particularly those already capable of inductively learning natural
language use.1
There is a widespread tendency in cognitive science to equate computation
(in particular digital computation) with information processing. It is hard to
find a comprehensive explicit account of information processing, which
explains concrete digital computation (rather than mathematical
computability). Still it is not uncommon to find descriptions of digital
computers as information processing systems proper. Such descriptions take
it for granted that digital computation presupposes information processing.
The Information Processing account seems like a natural candidate to explain
digital computation. After all, digital computers traffic in data. But when
‘information’ comes under scrutiny, the standard account becomes a less
obvious candidate. ‘Information’ may be interpreted semantically and non-
Reviewer
1
N/A
Reviewer
2
N/A
Ian
Sillitoe
David
Gamez
Hector
Zenil
Steve
Torrance
4
Leighton
Evans
Department
of Political
and Cultural
Studies
(Swansea)
5
Raffaela
Giovagnoli,
Pontifical
Lateran
University
(Rome)
semantically, and its interpretation has direct implications for Information
Processing as an account of digital computation. This paper deals with the
implications of these interpretations for explaining concrete digital
computation in virtue of information processing. To begin with, I survey
Shannon’s classic theory of information, and then examine how ‘information’
is used in computer science. In the subsequent section, I evaluate the
implications of how 'information' is interpreted for explaining concrete
computation. The key requirements for a physical system to compute, on an
Information Processing account, are then fleshed out, as well as some of the
limitations of such an account. Any Information Processing account must
embrace an algorithm-theoretic apparatus to be a plausible candidate for
explaining concrete digital computation.
Object-oriented
I argue that the category of equipment denoted computational objects have,
philosophy – the
by virtue of the unique presence of those objects in the world as permanently
nature of the
withdrawn from full disclosure of operation due to their dependence on
relations
computational code, a unique manner of causal interaction with users that
between humans
can only be described as vicarious. As computational devices become
and computational increasingly ubiquitous as tools for managing and navigation the human
objects
world, this vicarious relationship becomes important in understanding how
this technology affects the phenomenological experience of being in the
world as it is, alongside computational objects, and how orientation towards
the world can be described as computational.
Computational
Some formal aspects of human reasoning, as Brandom shows in the second
Rationality and
chapter of Between Saying and Doing (Oxford University Press, Oxford,
Religious Beliefs
2008), can be elaborated by a Turing Machine (TM) namely by a machine that
simulates human reasoning. But what can’t be elaborated either by Artificial
Intelligence and by Computational Intelligence is the content of beliefs. I
would like to present an example of the impossibility of elaborating the
content of human beliefs. It concerns religious beliefs. I’ll discuss the
following point: 1. I explain the phenomenon of “Bootstrapping” in the
pragmatic context, which shows how from basic practices described by a
“metavocabulary” new practices and abilities characterized by a new
Steve
Russ
Mark
Sprevak
David
Gamez
Raymond
Turner
6
Jiri
Wiedermann,
Institute of
Computer
Science
(Academy of
Sciences of
the Czech
Republic)
Beyond
Singularity
7
Rafal
Urbaniak,
Centre for
Logic and
Philosophy of
Science
Ghent
University,
Belgium
Florent
Franchette,
PhD student,
Paris in
France.
Randomness,
Computability,
and Abstract
Objects
8
Why is it
necessary to build
a physical model
of
hypercomputation
vocabulary emerge. The elaboration of certain aspects of practices and
abilities by a Turing Machine is an example of pragmatic bootstrapping. 2. I
clarify why human beliefs (in our case, religious beliefs) can’t completely be
elaborated either by Artificial Intelligence or by logic through material
inferences embedded in conditionals as they have peculiar contents.
Using the contemporary view of computing exemplified by recent models and
results from non-uniform complexity theory, we investigate the
computational power of cognitive systems. We show that in accordance with
the so-called Extended Turing Machine Paradigm such systems can be seen as
non-uniform evolving interactive systems whose computational power
surpasses that of the classical Turing machines. Our results show that there is
an infinite hierarchy of cognitive systems. Within this hierarchy, there are
systems achieving and trespassing the human intelligence level.We will argue
that, formally, from a computation viewpoint the human level intelligence is
upper-bounded by the _2 class of the arithmetical hierarchy. Within this class,
there are problems whose complexity grows faster than any computable
function and, therefore, not even exponential growth of computational power
can help in solving such problems.
Olszewski [21] claims that the Church-Turing thesis can be used in an
argument against platonism in philosophy of mathematics. The key step of his
argument employs an example of a supposedly effectively computable but not
Turing-computable function. I argue that the process he describes is not an
effective computation, and that the argument relies on the illegitimate
conflation of effective computability with there being a way to find out.
A model of hypercomputation is able to compute at least one function not
computable by Turing Machine and its power comes from the absence of
particular restrictions on the computation. Actually, some researchers defend
that it is possible to build a physical model of hypercomputation called
\accelerating Turing Machine\. But for what purposes these researchers
Murray
Shanaha
n
Kevin
Magill
John
Preston
Barry
Cooper
Barry
Cooper
Hector
Zenil
Philosophy of
computing/
hypercomput
ation
9
William (Bill)
Duncan,
Graduate
student,
Buffalo
Using Ontological
Dependence to
Distinguish
Between
Hardware and
Software
10
Michael
Nicolaidis,
TIMA
Laboratory
Grenoble,
On the State of
Superposition and
the Parallel or not
Parallel Nature of
Quantum
would try to build a physical model of hypercomputation when they already
have mathematical models more powerful than the Turing Machine? In my
opininon, the computational gain of the accelerating Turing Machine is not
free. This model also lost the possibility for a human to access to the
computation result. To define this feature, I'll propose a new constraint called
the \access constraint\ stating that a human can access to the computation
result regardless of computation ressources. I'll show that the Turing
Machine meets this constraint unlike the accelerating Turing Machine and I'll
defend that build a physical model of the latter is the solution to meet the
access constraint.
The distinction between hardware and software is an ongoing topic in
philosophy of computer science. We often think of them as distinct entities,
but upon examination it becomes unclear exactly what distinguishes the two.
Furthermore, James Moor and Peter Suber have cast doubt on the idea that
there is a worthwhile distinction. Moor has argued that the distinction should
not be given much ontological significance. Suber has argued that hardware is
software. I find both these positions implausible, for they ignore more general
ontological distinctions that exist between hardware and software. In this
paper, I examine the arguments of Moor and Suber, and show that, although
their arguments may be valid, they draw implausible conclusions. The
ontological perspectives on which their arguments are based are too narrow,
and the ontological distinctions used to motivate their arguments are not
applicable to reality in general. I then argue that distinctions do emerge
between hardware and software when they are considered using ontological
distinctions that have wider applicability: A piece of computational hardware
is an ontologically independent entity, whereas a software program is an
ontologically dependent entity.
In this paper we use ideas coming from the field of computing to propose a
model of quantum systems, which gets rid of the concept of superposition
while reproducing the observable behaviour of quantum systems as
described by quantum mechanics. On the basis of this model we contest the
interpretation of quantum mechanics based on the so-called quantum
Ian
Sillitoe
Murray
Shanaha
n
Steve
Russ
Tillmann
Vierkant
France
Computing: a
controversy
raising point of
view
11
Paul
Schweizer,
Edinburgh,
Informatics
Multiple
Realization and
the Computational
Mind
12
Tom Froese
From
Artificial
Life to Artificial
Embodiment:
Using
humancomputer
interfaces
to
investigate
the
embodied
mind
'as-it-could-be'
from the firstperson
perspective
13
Li Zhang,
School of
Computing,
Univ. of
Contextual Affect
Modeling and
Detection from
Open-ended Text-
superposition and the related parallel-computing interpretation of quantum
algorithms. The goal of this presentation is to bring for discussion in the
conference ontological arguments against the so-called quantum parallelism,
which are mutually supported with recent advances in complexity analysis of
quantum algorithms.
The paper examines some central issues concerning the Computational
Theory of Mind (CTM) and the notion of instantiating a computational
formalism in the physical world. In the end, I argue that Searle’s view that
computation is not an intrinsic property of physical systems, but rather is an
observer relative attribution, is correct, and that for interesting and powerful
cases, realization is only ever a matter of degree. And while this may fatally
undermine a computational explanation of conscious experience, it does not
rule out the possibility of a scientifically justified account of propositional
attitude states in computational terms.
There is a growing community of scientists who are interested in developing
a systematic understanding of the experiential aspects of mind. We argue that
this shift from cognitive science to consciousness science presents a novel
challenge to the fields of AI, robotics and related synthetic approaches. While
these fields have traditionally formed the central foundation of cognitive
science and led the way toward new views of cognition as embodied, situated
and dynamical, in the current turn toward the experiential aspects of mind
their role remains uncertain. We propose that one way of dealing with the
challenge is to design artificial systems that put human observers inside
novel kinds of sensorimotor loops. These technological devices can then be
used as tools to investigate the embodied mind ‘as-it-could-be’ from the firstperson perspective. We illustrate this methodology of artificial embodiment
by drawing on our recent research in sensory substitution, virtual reality and
large-scale interactive installations.
Real-time contextual affect detection from open-ended text-based dialogue is
challenging but essential for the building of effective intelligent user
interfaces. In this paper, we focus on context-based affect detection using
emotion modeling in personal and social communication context. Bayesian
Kevin
Magill
Susan
Stuart
Mark
Bishop
John
Preston
Raymond
Turner
Slawomir
Nasuto
Teesside
based Dramatic
Interaction
14
Kevin Magill,
Philosophy,
Wolverhampt
on; Yasemin J.
Erden,
CBET/Philoso
phy, St Mary’s
University
College
Autonomy and
desire in machines
and cognitive
agent systems
15
Mark Bishop
& Mohammad
Majid alRifaie,
Goldsmiths
Simon Colton
& Alison
Pease
Creativity?
16
Computational
Creativity
networks are used for the prediction of the improvisational mood of a
particular character and supervised & unsupervised neural networks are
employed respectively for the deduction of the emotional implication in the
most related interaction context and emotional influence towards the current
speaking character. Evaluation results of our contextual affect detection using
the above approaches are provided. Generally our new developments
outperform other previous attempts for contextual affect analysis. Our work
contributes to the conference themes on sentiment analysis and machine
understanding
The development of cognitive agent systems relies on theories of agency,
John
within which the concept of desire is key. Indeed, in the quest to develop
Barnden
increasingly autonomous cognitive agent systems desire has had a significant
role. Yet we maintain that insufficient attention has been given to analysis
and clarification of desire as a complex concept. Accordingly, in this paper we
will discuss some key philosophical accounts of the nature of desire, including
what distinguishes it from other mental and motivational states. We will then
draw on these theories in order to investigate the role, definition and
adequacy of concepts of desire within applied theoretical models of agency
and agent systems.
Yasemin
Erden
Yasemin
Erden
Mark
Sprevak
Kevin?
Nasuto?
Colton?
Mark
Bishop
Programme Committee (for reviewing):
Mark Bishop
Steve Russ
Kevin Magill
Yasemin J. Erden
1. Prof. Ian Sillitoe (Wolves; robotics)
2. Dr David Gamez (Essex; computing/philosophy)
3. Dr Hector Zenil (Wolfram Research; computer science)
4. Dr Slawek (Slawomir) Nasuto (Reading; cybernetics) –(have sent only one for review, without a request for just one)
5. Professor Murray Shanahan (Inperial; computing)
6. Professor Raymond Turner
(Essex; logic/computation)
7. Professor Steve Torrance (Sussex; informatics/philosophy)—consciousness symposium organiser! (one paper only)
8. Dr John Preston (Reading; philosophy/AI)
9. Professor John Barnden (Birmingham; AI/metaphor) –(have sent only one for review, without a request for just one)
10. Professor Barry Cooper (Leeds; mathematics)
11. Dr Mark Sprevak (Edinburgh; philosophy of mind etc)
12. Dr Susan Stuart (Glasgow; philosophy/technology)—(one paper only if possible, two maximum)
13. Dr Tillmann Vierkant (Edinburgh; philosophy of mind)—(one paper only if possible, two maximum)