Tag Archives: sustainability

Inspiration for the Future from AAAI 2012

AAAI 2012 has gone for another year and it was a great conference by all accounts, as long as you stayed out of the Toronto heat. In an upcoming post we’ll have a more a detailed overview of the papers from the Computational Sustainability track. One thing most attendees would probably agree on was that this year’s plenary speaker’s lineup was fantastic. I found a few of the plenary talks particularly inspiring for the future of AI as well for Computational Sustainability research even though the talks were not focussed on that topic:

  • Judea Pearl was awarded the highest honour in Computer Science, the ACM Turing Award, for 2011 and he chose to give his ACM Turing Lecture at AAAI 2012. He provided a fascinating history of research into inference and causal learning. He argued that counterfactual reasoning is the best basis to create ‘mini-Turing tests’ since humans naturally and effortlessly carry out counterfactual reasoning all the time. Yet it is something that is still not widely used in modelling and AI systems.  Advances in causal inference and learning would of course be a huge benefit for all scientific pursuits. In sustainability sciences in particular, there is a huge amount of data collection being carried out and discovering causal relationships in this data (such as between native organisms and invaders, climate change and pollutants, policies and energy usage) are the core challenges in these fields. Algorithms and usable tools that scientists can use to more quickly test their causal hypothesis’ or discover new possible causal relationships would have a huge impact.
  • Christos Papadimitriou gave the AAAI Turing Lecture, which was an inspiring and very personal talk on the contributions of Alan Turing on this 100th anniversary of his birth. Papadimitriou compared Alan Turing to Charles Darwin as a founder of a field but also as a major contributor to the understanding of biology and evolution.  He described how computer science is transforming the fields of biology and genetics. One example are some recent results from his research group applies theoretical CS analysis to resolve the conundrum of sexual recombination in genetics. The problem, as I understand it, is that asexual recombination works perfectly well in many simple organisms, optimizing fitness as the number of offspring produced. So the question is, why do more complex organisms use sexual recombination? Why do they require two individuals when one seems to work perfectly well?  Their analysis and experiments show that sexual recombination is optimal if the fitness measure isn’t the number of offspring produced but rather, the ability to breed widely. Thus, robustness of breeding is being favoured over maximizing offspring. This is something which has apparently been hard for geneticists to work out from their point of view but from a computational perspective was more easily achievable.  The message from this being that we should never underestimate what contributions computer science can make to other fields of human knowledge. Even theoretical concepts can turn out to provide a better understanding of something in the world; but we as computer scientists need to reach out and make the connections ourselves, because it is unlikely else will.
  • Sebastian Thrun later spoke about the Google self-driving car project which he is a part of. It was a great update on how far Google has come in a remarkably short time towards a feasible self-driving car that can be used on a large scale. Attendees had a bit of an insider view of some of their latest results a few weeks before the media ran stories on Google making more confident announcements about how reliable their cars are compared to human drivers (spoiler: the self-driving cars are more reliable). As Thrun pointed out in his talk, there are still a small percentage of cases where the human driver needs to take over but under normal driving conditions these situations come  up on the order of every few months rather than hours or days. One obvious connection between self-driving cars and sustainability is energy efficiency. If a critical mass of cars on the road are self-driving then many options become possible such as coordinated traffic, drafting to increase fuel efficiency and more dynamic carpooling. Thrun pointed out that if you look at the utilization of roads in the USA very little of the space is actually used at any one time. Self-driving cars could tailgate much more closely and thus reduce the need to build more roads into existing natural areas. But the other lesson I took away from this is that along the way to attacking the problem of  self-driving cars they encountered challenging open problems, such as : how to combine huge amounts of data from heterogeneous sensors; how to dynamically switch datasources in real time when one system failed (eg. when the maps are out of date due to road construction); complex problems of spatial reasoning about the identity of objects showing up on the laser scanner (ie. is it a tree, another car or a person?).  Of course, all of this also needs to be done in real time with a very, very low failure rate because lives are on the line. By forcing themselves to deal with all these challenges at once in search of an ambitious goal they needed to find new solutions for visualization, learning, optimization and data management. I think one of the big Computer Science gains of Computational Sustainability research is a similar necessity of invention that arises from dealing with problems which are larger, more noisy or more heterogeneous than a simpler test domain would provide.
The CompSust track talks themselves were varied and fascinating. The interesting thing about CompSust sessions is that the computational methods can vary widely within a single session. The organizing topic, such as “spatiotemporal environmental modeling” for example, could hold together research utilizing hierarchical Gaussian processes, graph cut optimization and image segmentation.  The poster sessions were, of course, where all the real discussion happened and the CompSust aisles were heavily frequented from what I saw. You can find the full program here and we’ll have a more thorough review of the papers coming later.
What was your favourite part of the conference AAAI2012? Let us know in the comments.

Upcoming Deadlines

A regular list of upcoming workshops, courses, conferences and deadlines of relevance the CompSust community, if we’re missing something let us know!:

  • Workshop : CROCS at CP-12 – Otherwise known as the Workshop on Constraint Reasoning and Optimization for Computational Sustainability. This will be the 4th annual instantiation of the workshop. It’s a good opportunity to connect CompSust research with the constraint and optimization communities and as a bonus it’s in beautiful Quebec City.
  • Course : MOOC on Sustainability – Continuing the trend of large, free online courses (apparently we’re calling them Massively Online Open Courses (MOOC) now) the University of Illinois is providing a MOOC on Sustainability. So if you’re a computer scientist looking to get into sustainability problems and want a crash courses this is a cheap way to do it.
  • Journal deadline : Special Section on Computational Sustainability in IEEE Transactions on Computers (deadline: Oct 1, 2012)
  • Journal deadline : Machine Learning Journal Issue on Science and Society issue (deadline: Nov 16, 2012) : sustainability and the environment (ecology, smart grids, etc.) listed amongst the example topics.

Community

Check out the growing list of community resources for more news and announcements, especially the mailing list. If you know about other news/conferences/deadlines/links of interest, feel free to share them with us and the community:

Computational Sustainability at AAAI-12

Next week is the next event in the summer of CompSust conferences. The Twenty-Sixth Conference on Artificial Intelligence (AAAI-12) is being held next week (July 22-26) in Toronto, Canada. So here’s a little preview of what to expect and how to get the most out of it.

The schedule for the entire conference can be found here. To get a taste of the kind of topics being covered you can take a look at  this excellent review of the papers from last year (complete with an handy chart) by Douglas Fisher from Vanderbilt University. Note that one of the two best papers from the entire conference was from the CompSust Track (“Computational Sustainability and Artificial Intelligence Track: Dynamic Resource Allocation in Conservation Planning” by Daniel Golovin, Andreas Krause, Beth Gardner, Sarah J. Converse, Steve Morey).

CompSust track papers from last year's AAAI-11. Courtesy of Douglas Fisher.

There isn’t a handy chart for this year’s conference yet but a quick look at the topics shows that many of the same topics will be covered as well as some new additions. A brief look at the sustainability topics includes: modelling climate change, ocean eddy monitoring, air pollution, forest management, wildlife conservation design, invasive species and infectious disease control,  power grid management and battery output prediction and control. Just from the titles the range of computational methods used includes at least : linear programming, Q-learning, Lagrangian relaxation, Inverse RL and Bayesian ensemble prediction.

Of course the point of having this track at the AAAI conference is to help broaden the field of AI research and showcase a large cluster of multi-disciplinary collaboration that is already going on. I can tell you that from last year’s conference, the CompSust sessions have a different feel than the other parallel tracks since there are a variety of computational methods being discussed within the same session whether it be on energy management or ecological planning. So if you want a change of pace from the method focussed tracks consider stopping by a CompSust session.

Twitter

This conference will also be the launch of the official Twitter account for the Computational Sustainability field, @compsust. So follow us at @compsust for the latest updates on the conference or search for the #compsust or #aaai12 tags for posts about what interesting research people are talking about and share your own thoughts.

Google+

For discussion that needs more than 140 characters  you could also sign up for the Google+ event for the whole AAAI conference where you can discuss anything going on and meet up with people.

Mailing List

If you aren’t already on the yahoo groups mailing list for computational sustainability make sure you subscribe. There are announcements about conferences, journal deadlines and relevant science news for the community.

That’s all for now. See you next week!

Tusind Tak Copenhagen!

So the CompSust2012 Conference is over and our mixed band of computer scientists, ecologists, operation researchers, engineers, urban planners (and more) are dispersing back to their homes in Denmark, Jordan, Uganda, Italy, the Netherlands, France, Germany, Ireland, the UK, the Netherlands, Switzerland, Canada and the USA (and that’s just people I talked to, who am I missing?).

I think everyone would agree it a was a very well run conference and very productive. Over powerpoint slides, posters, food and even beer we all gained insights into challenging computational and sustainability problems and topics we probably didn’t know about before we came.

We all know finding ways to improve the sustainability is full of important and challenging problems, but it a different thing to see exactly what people are struggling with around the world and what solutions they have found.

For example, did you know that…

  • if you count of all the wireless devices people have access to that the locations of about one third humanity is knowable in principle? Paul Luckowicz described this and other amazing facts about what he calls our digital shadows to us during his Master class discussion on Wednesday. This data can be used for good or for ill but it will be used; so it’s best to start thinking and planning for it, that’s what his FuturICT project is looking at.
  • the widespread use of Linear programming techniques for policy making was essentially kickstarted in the 1970s by the success of these methods at predicting the end of oil independence in US as demand grew? Warren Powell gave a rousing and thought provoking Master class seminar on the broad area of stochastic optimization in dynamic domains and described how he believes a broad range of methods from different communities can work together if there is increased communication between researchers.
  • in Uganda, smart phones with internet connectivity are becoming so common it is assumed that most research projects using technology to help with sustainability will utilize them? So that’s what John Quinn is doing. His machine learning group in Uganda is creating solutions for automated data collection and disease diagnosis using Android phones to augment the restricted access to trained experts on the ground. Their applications range from malaria detection, to plant disease spread to traffic monitoring.
  • owning and powering a fully electric car uses about as much power as an entire household? Hartmut Schmeck pointed out that the concern is not just that this costs a lot of money or uses energy, but also puts a huge new load on power systems already at their maximum level at the local distribution level. Several talks friday morning by Nick Jennings, Hartmut Schmeck and Holger Hermanns described these kinds of power grid challenges in the UK, Germany and elsewhere. The good news is there are ways to make this manageable if we are smart about it. The really good news is there are challenging computational research problems about how to do that.
  • some day your house might be able to learn it own customized weather forecast? It will do this by tracking the actual weather outside and learning how it drifts from the predicted regional forecasts, allowing your house to better manage it’s energy usage. This is one of the projects Nick Jennings is working which he talked about in his plenary talk.
  • some day consumers may be able to band together to demand better or more sustainable policies from their service providers such as power companies? Well, that’s already happening and researchers are using the techniques of co-operative game theory to work out how it would work.

This is just a sample of some of the topics from the plenary talks alone, there were also great parallel track talks on energy management, species distribution modeling and conservation planning, water management, social analysis and incentives and how to integrate computational sustainability into computer science education.

The full program can be found here and many of the slides from talks will be up on line at the conference website when they become available.

Finally, I’ll end this little summary where Carla Gomes began the conference, with her inspiration for the field of Computational Sustainability. She described it as being part of the evolution of Computer Science into what could be considered a third age. The first age included working out the practicalities or hardware, computation and networks; the second included, among other things, the creation of the powerful abstractions of artificial intelligence and machine learning. The third age involves these and other advances of computer science reaching out an integrating with other disciplines to bring the power of computational thinking to bear on the world’s most challenging problems.

Few problems are more challenging than how to make our growing civilization sustainable on the finite resources of the Earth; but that is what Computational Sustainability faces and it looks like we’re well on our way to contributing to meeting this challenge.

If you went to CompSust2012 keep the discussion going :

CompSust Summer Conference Preview

It’s going to be an exciting summer.

There is tremendous research happening around the world attempting to bridge the gap between computational fields such as artificial intelligence, constraint programming, optimization and machine learning with scientists carrying out research in fields such as ecology, sustainability, climate systems, power planning.

This collaborative research goes under many different names such as Computational Sustainability, Ecosystem Informatics, Sustainable Computing and Climate Informatics but they all share the idea that there is enormous potential sitting at the intersection between the latest computational research and the effort to improve the sustainability of human society in the broadest possible sense.

In an effort to get this blog kickstarted I thought I’d write the itinerary for some very ambitious CompSust researcher who wanted to see it all over the summer. (Although I suppose you should be sure to buy lots of carbon offsets…)  If there are others I’m missing (likely), feel free to let me know in the comments.

The first stop would have been a few weeks ago in San Diego at the International Green Computing Conference which looked at both sides of the Computing/Sustainability coin by bringing together researchers in the “fields of sustainable and energy-efficient computing, and computing for a more sustainable planet”.

Next up, you could head over to Edinburgh for ICML2012 at the end of June. ICML will have some focus on machine learning for sustainability including an invited talk by David MacKay on using machine learning to make sure the challenges of climate change and sustainable energy management are faced head on with reliable numbers.

The following week, it’s a short hop over to Copenhagen, Denmark for Computational Sustainability 2012 which starts with a day of Master Class Seminars by leaders in the field on existing results and problem domains followed by two days of the latest research. The schedule isn’t out yet but the topics promise to include research on computational approaches to land use planning, climate modelling and natural resource and energy planning.

AAAI2012 is in Toronto this year and once again running a special track on Computational Sustainability. A brief look at the sustainability topics includes: modelling climate change, ocean eddy monitoring, air pollution, forest management, wildlife conservation design, invasive species and infectious disease control,  power grid management and battery output prediction and control. Just from the titles the range of computational methods used includes at least : linear programming, Q-learning, Lagrangian relaxation, Inverse RL and Bayesian ensemble prediction.

In September you could then head over to Boulder, Colorado for the Climate Informatics 2012 conference which will bring together researchers in machine learning working specifically on the problems of climate modelling. Part of the focus is to brainstorm ideas on how to accelerate progress on climate change questions as well as discover challenging new domains to push existing machine learning approaches.

Finally in October (ok, this is well out of the summer, but still) there is the International Workshop on Constraint Reasoning and Optimization for Computational Sustainability (CROCS-12) in Quebec City. You even still have time to submit for that one, Quebec City should be very nice in October…before the snow comes.

Some other events can also be found on the CompSust page at the CRA.

I’m planning on writing up some highlights from the CompSust2012 and AAAI conferences this summer so if there is something fantastic you see there, at another conference or elsewhere let us know in the comments.