Now showing items 1-6 of 6
Co-evolutionary analysis: a policy exploration method for system dynamics models
(System Dynamics Society / Wiley, 2012-10-22)
In system dynamics (SD), complex nonlinear systems can generate a wide range of possible behaviours that frequently require search and optimization algorithms in order to explore optimal policies. Within the SD literature, ...
A learning architecture for scheduling workflow applications in the cloud
The scheduling of workflow applications involves the mapping of individual workflow tasks to computational resources, based on a range of functional and non-functional quality of service requirements. Workflow applications ...
The influence of random interactions and decision heuristics on norm evolution in social networks
In this paper we explore the effect that random social interactions have on the emergence and evolution of social norms in a simulated population of agents. In our model agents observe the behaviour of others and update ...
Particle swarm optimisation with gradually increasing directed neighbourhoods
(Association for Computing Machiner, 2011)
Particle swarm optimisation (PSO) is an intelligent random search algorithm, and the key to success is to effectively balance between the exploration of the solution space in the early stages and the exploitation of the ...
Observations on the shortest independent loop set algorithm
(System Dynamics Society / Wiley, 2012-07-31)
The shortest independent loop set (SILS) algorithm is a widely adopted loop selection method in eigenvalue elasticity analysis to identify dominant loops. However, we find that, in an individual-based model, the SILS cannot ...
Applying reinforcement learning towards automating resource allocation and application scalability in the cloud
Public Infrastructure as a Service (IaaS) clouds such as Amazon, GoGrid and Rackspace deliver computational resources by means of virtualisation technologies. These technologies allow multiple independent virtual machines ...