Bath Artificial Intelligence (BAI) Seminar is a
research and discussion group. Announcements are made in the BAI mailing
list, which also has its own archive.
to Bath and a campus map: Computer
Science is in 1W, beside the
library. Upcoming talks are listed below and announced by
Williamson & William
Bath's 2009 Autonomous Underwater Vehicle
making for autonomic solutions on the Grid
Development and Analysis of Conscious
The talk will start by situating work on machine consciousness within
the broader framework of the scientific study of consciousness. The
specific problems raised by machine consciousness will then be
covered, along with the extent to which we can make accurate
predictions about the consciousness of machines. Next, experimental
work will be summarized, in which a spiking neural network was used to
implement models of imagination and emotion that controlled the eye
movements of the SIMNOS virtual robot. This network had several
cognitive functions that have been linked to consciousness, and
predictions were made about the consciousness of the network using the
theories of Tononi, Aleksander and Metzinger. The talk will conclude
with some of the applications of this work to the scientific study of
consciousness and cognitive engineering.
||A Primer on AI for
Domestic Robots: Does Thinking Help?
individuality to phenotypic plasticity in
Natural selection requires
variation to operate – there is no change without options to
select between. Variation is therefore itself subject to
selection, including its rate and extent. Individual plasticity
(including cognition) is known to facilitate evolution in two
ways. First, it accelerates evolution when a species is far
enough from its local optima that even unreliable processes like
individual learning provide evidence that genetic evolution can exploit
about which animals are closer to optimal. But second, plasticity also
slows genetic convergence once the adaptive phenotype is close enough
to genetic specification that individuals can reliably learn to be
`fit’. This reliability reduces selective pressure, and
thus retains diversity. Here we present an extension to a classic model
of the interaction between plasticity & natural selection (Hinton
& Nowlan 1987), to examine whether increased genetic variation in
offspring can play a similar role to individual plasticity. We find
that a higher recombination rate significantly accelerates the earlier
phase of the model, where the organism is ill-suited to its environment
and deleterious traits require elimination from the genome. This
indicates that genetic variation plays a role similar to plasticity in
this stage. We speculate that a behavioural search for identity
in social species may play a similar role.
emotion and neural networks
In a conscious experience, attention selects the elements in the
environment that will undergo further processing. Emotion influences this
mechanism by evaluating the significance of the stimuli perceived, and by
contributing to the ensuing phenomenology. I investigated the intricacies of
this system through two experimental paradigms: the modulation of the
attentional blink by emotion-laden information, and a psychophysical
paradigm studying the mechanisms responsible for the automatic processing of
this information. I used the results of this work to inform theories, and
sketched out a model of the neural basis underlying the attentional blink.
With a view to investigating this proposal through modelling, I participated
in the development of NeMo, a platform for the real-time Neural Modelling of
spiking neurons using GPUs. If time permits, I will also present the award
winning project I led at the Barcelona Cognition, Brain & Technology summer
school this year, investigating emotional conditioning of the humanoid robot iCub.
Roesch, E. B., Sander, D., and Scherer, K. R. (2007) The link between
temporal attention and emotion: A playground for psychology, neuroscience,
and plausible artificial neural networks. In J. Marques de Sa et al. (eds.),
Proceedings of the International Conference on Artificial Neural Networks, volume 2; pp 859-868.
Fidjeland, A., Roesch, E. B., Shanahan, M. P., Luk, W. (2009). NeMo:
A platform for Neural Modelling of spiking neurons using GPUs. 20th IEEE
International Conference on? Application-specific Systems, Architectures and Processors.
Roesch, E. B., Sander, D., Scherer, K. R. (in press). Emotion and
motion in facial expressions modulate the attentional blink. Perception.
the application of agent based modelling
in behavioural ecology
In this talk a set of models will be presented which test the effects of different
variables on the evolution of social dominance and social hierarchy in gregarious
animals. These variables are on the one hand environmental pressures like predation
and different rates of food availability, and on the other selective mechanisms like female
mate choice and matrilineal dominance inheritance. The talk will also give an overview
of the potentials and limits of the usage of agent based models in the field of behavioural ecology.
Making in the Brain
It has recently become clear
that humans and animals feature statistically near-optimal performance
in common low-level tasks, and also show use of statistical information
in various high-level tasks. This implies that the brain is able to
perform the computations that underlie statistical inference, but it
remains unclear exactly how and where this computation is performed.
The aim of this talk is to give a broad overview over some areas where
statistical optimality is observed, and to provide a more detailed
discussion about investigating optimality of behaviour in tasks that
require decision making under time constraints. In such tasks the
decision maker needs to, firstly, accumulate uncertain information, and
to, secondly, make a decision once sufficient evidence is available.
Regarding the accumulating stage I will discuss the optimal strategy,
neuronal measurements and computational models that attempt to explain
these measurements. The problem of when to commit to a decision will be
addressed purely from the optimality point-of-view, by describing the
optimal strategy and comparing it to human and animal behaviour. I will
present both standard approaches available in the literature and
recently published and yet-to-be-published work performed by myself and
others in my lab.
Modelling4All Project: A web-based modelling tool