project aims to develop techniques, methods and architectures for
modelling, designing and building decentralised systems that can bring
together information from a variety of heterogeneous sources in order
to take informed actions. To do this, the project needs to take a total
systems view on information and knowledge fusion and to consider the
feedback that exists between sensing, decision making and acting in
such systems. Moreover, it must be able to achieve these objectives in
environments in which: control is distributed; uncertainty, ambiguity,
imprecision and bias are endemic; multiple stakeholders with different
aims and objectives are present; and resources are limited and
continually vary during the systemâs operation.
More specifically, the main aims of the project are:
To devise techniques that enable an actor to effectively
balance acting and information gathering in dynamic,
uncertain, multi-actor environments.
To devise techniques that enable an actor to fuse, in a
decentralised manner, inter-related information that is
uncertain, incomplete, imprecise and ambiguous.
To develop machine learning algorithms that are
efficient and effective in dynamic, multi-actor
environments that are uncertain and incomplete.
To develop coordination mechanisms that enable
collectives to plan and act collaboratively in order to
achieve common goals.
To develop methods for modelling and predicting the
system behaviour that will ensue from specifications of
the local behaviour of the individual actors.
To develop mechanisms that ensure desirable overall
properties emerge based on local actions and views.
To develop decentralised system architectures that can
operate effectively in uncertain and dynamic
environments and that are robust, scaleable and flexible
in their operation.
ensure the specific methods and techniques developed in the research
fit together to give a coherent whole, the project will develop a
number of software demonstrations. These will be in the broad area of disaster management.