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Natural Disasters And Early Warning Systems In Australia, Emma Papaemanuel, Katina Michael, Peter Johnston

Professor Katina Michael

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Are Disaster Early Warnings Effective?, Kerri Worthington, Katina Michael, Peter Johnson, Paul Barnes

Professor Katina Michael

Australia's summer is traditionally a time of heightened preparation for natural disasters, with cyclones and floods menacing the north and bushfires a constant threat in the south. And the prospect of more frequent, and more intense, disasters thanks to climate change has brought the need for an effective early warning system to the forefront of policy-making. Technological advances and improved telecommunication systems have raised expectations that warning of disasters will come early enough to keep people safe. But are those expectations too high? Kerri Worthington reports. Increasingly, the world's governments -- and their citizens -- rely on technology-based early warning …

Concern People Without Latest Technology Will Miss Fire Warnings, Sally Sara, Ashley Hall, Peter Johnson, Katina Michael

Professor Katina Michael

But what if the website goes down in the way Victoria's Country Fire Authority website crashed as fires raged a few weeks ago? What about those people who don't own the latest technology? And what happens when the power goes out?

KATINA MICHAEL: Well there's no television, there isn't ability to access the internet potentially.

ASHLEY HALL: Professor Katina Michael is Associate Professor at the School of Information Systems and Technology at the University of Wollongong.

KATINA MICHAEL: I would suggest a long lasting powered radio because we don't want is we don't want when the lights go out, or …

Delayed Observation Planning In Partially Observable Domains, Pradeep Reddy Varakantham, Janusz Marecki

Research Collection School Of Computing and Information Systems

Traditional models for planning under uncertainty such as Markov Decision Processes (MDPs) or Partially Observable MDPs (POMDPs) assume that the observations about the results of agent actions are instantly available to the agent. In so doing, they are no longer applicable to domains where observations are received with delays caused by temporary unavailability of information (e.g. delayed response of the market to a new product). To that end, we make the following key contributions towards solving Delayed observation POMDPs (D-POMDPs): (i) We first provide an parameterized approximate algorithm for solving D-POMDPs efficiently, with desired accuracy; and (ii) We then propose …

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