Welcome and introduction

Hello internet, and welcome to a humble blog about my life as a PhD student, which should hopefully contain a great deal of thoughts and musings on the work I've got myself into for the next three years. The purpose of this is twofold: firstly, this provides me somewhere to share what I understand from reading and learning about the algorithms I'm supposed to be dealing with: and by extension a place for people to tell me how wrong I am. Secondly in the unlikely event you have a vested interest in my life you can use it to keep track of what I'm doing over the next few years.

As a brief summary overview, following my graduation with an MPhys in Physics, I'm now being funded for a PhD in computer science from something called the Orchid Project. This is a big collaboration of companies and Universities which work together in three specific areas of computer science, under the broad umbrella of "Agents".

I have to admit I had no idea what an "agent" was until I went to a seminar on available PhDs. In broad terms, as I understand it an agent is essentially a distinct unit of computation which can act independently and (in the sense that they can be intelligent) autonomously to achieve certain tasks in an environment, and in the presence of other such agents. This actually makes the field extremely broad: covering things from smart-thermostats or forms of bidding software, to fully fledged autonomous unmanned-aerial-vehicles (UAVs).  Specifically Orchid focusses on Smart Grid (energy distribution) work, Citizen Science (which involves crowdsourcing), and Disaster Relief. It was this latter area which piqued my interest; not least because the method they plan on using involves deploying intelligent agents in the form of UAVs to assist first-responders and emergency services in disaster situations; for example earthquake zones.

Orchid is looking to have the UAVs act autonomously: removing the need for that clunky remote control.

The ultimate goal looks something like this: in the event of a disaster, a fleet of UAVs is deployed into the sky above the area. Thereafter, emergency services will have a PDA or smartphone app of some sort, with which they can request imagery of a particular area from the UAVs (which are equipped with cameras), whilst also specifying things like urgency and duration required. This information is sent to the UAVs who then act autonomously to work out between themselves which vehicle goes to which task such that they achieve the best overall coverage that the emergency services need. Clearly they need to co-operate to achieve this.

This is no simple task, for a couple of reasons. Firstly, a great deal needs to be taken into account before simply deciding that UAV 1 will go and look at task 1. Obviously distance to the target is a factor, as well as the task's urgency, priority, and duration. Then there's the issue of battery life, ie. is it possible for the UAV to complete the task before running out of juice? Is it better to send 2 UAVs to the same task to try and maximise effectiveness?

Considering how tricky this exercise would be on paper, implementing them on UAVs is quite a challenge. The vehicles aren't exactly equipped with supercomputers, so computation has to be kept to a fairly simple level. There's also no central-computer to which they all connect. This means they can only compute by talking to each other; and of course the number of available UAVs, tasks, and PDAs is changing all the time. It's not good enough to make a decision and carry it out: the UAVs have to constantly update and check on what else is going on.

Anyway: co-ordinating the little beasts being the ultimate aim, there are (thankfully) some useful existing methods for getting them to work together nicely. I'll go into them in the next post. For now: that's what I'm hoping to contribute to. Let's see how it goes.

-C