Wednesday, October 30, 2013

Diverse mathematical biology

The last day for registration for the 5th Swedish Math-Biology Meeting is today. The meeting will take place in the first week in December.

What I think is cool when you look at the programme  is the diversity of subjects that will be talked about. The list includes everything from 'in-silico ecology and 'neural fields'', through 'fish stocks' and 'fossil dating' back to 'food webs', 'collective decision-making' and 'human fingers'. There is so much variety in how mathematics can be used to study biology.

Being optimistic, I should talk about the common language of mathematics linking all these diverse subjects together. And to some degree this is true. There are common processes in all these parts of biology that are captured by models. It is fun seeing how your favourite model can be used in a completely different way.

Being realistic, however, I know there are going to be a lot of confused (or sometimes sleepy) looks on our faces as we try (or fail) to understand what each other are doing. But that should never stop us from trying. See you in December.

Monday, October 28, 2013

Intelligence explosion and other nonsense.

It is always important to think about what we can and can't use models and theory to do. I work part time at the Institute for Futures Studies  in Stockholm. There we are using models to predict social change. When you have such ambitious goals it is important to be realistic. It's important not to exaggerate what we can hope to achieve.

This is why when I read on Olle Häggström's blog about the so called "Intelligence Explosion" I thought it might be useful to write something about futurology. The Intelligence Explosion is basically a set of arguments about why machines will one day be cleverer than us and what will happen once they are. You can read an intro here

So I wrote a short rhetorical piece on Olle's blog about: Why "intelligence explosion" and many other futurist arguments are nonsense. Olle wrote a reply and forced me to clarify a few things and I think the result is quite nice discussion.

I still think that Intelligence Explosion is nonsense, although fun nonsense. We should be careful what we say about the future. As Paul Gascoigne (and apparently Tony Blair too) once said “I never predict anything, and I never will”.

Thursday, October 24, 2013

Testing rules of thumb

Yesterday our paper on damselfish movements came out online. Its available online and open access, so download it as many times as you want.

This research started when James 'Teddy' Herbert-Read, Alex Jordan and Ashley Ward went up to the University of Sydney's One Tree Island field station on the Great Barrier Reef. Damselfish live on the coral reefs there and frequently have to decide when to move between the relatively safety of one bit of coral to another. Teddy set up an experiment to test how they make these moves, placing two bits of coral at either end of a long tank. Then he filmed and tracked the fishes movements back and forward.

Based on our previous work, we expected the fish to make these risky moves between coral together in small groups. This time we wanted to know more about the 'rule of thumb' they use to decide when to go. It turned out to be deceptively simple. Roughly speaking, it is "follow the last fish": if you are a fish on one of the corals then you are more likely to leave if another fish has just left. It appears that the total number of fish on the coral is less important than where the last move was made.

Recently, in our research, we have tried to become more precise in how we test which rules of thumb animals are using to make decisions. We use a method developed by Richard Mann for comparing how well different behavioural rules explain the data. In this case, the "follow the last fish" rule gave the most convincing model of the moves made by the fish. Other rules of thumb might give a better fit when we tune the parameters, but when we test the model robustness using Bayes factor, the "follow the last fish" rule gave the best predictions.

In the earlier study (I mentioned above) we had found that a different rule---"that the probability of leaving increases with number which have left"---fitted the data best. This worried me a bit at first, since we wouldn't necessarily expect the fish to use different rules in different contexts. Furthermore, Richard was pretty confident that if he used his method on the data from the earlier study then he would get a better fit with the new, simpler "follow the last fish" rule. It was with some trepidation I emailed him the data from the earlier study. It isn't fun to have to admit you might have got it wrong, especially after something is published!

But it turned out my rule still came out top when he calculated Bayes factor on the older experiments. The differences in the experimental setup, and probably differences in the risks perceived by the fish, mean that the fish that they use different rules in different contexts.  You can find out more by reading the paper!

Sunday, October 20, 2013

Putting the person in to the particle

Over the last decade physicists have developed “social force” models to describe the movement of individuals in crowds and gatherings. These models assume rather simple repulsion/attraction interaction forces to explain how people behave in these situations. They may be useful in, for example, designing escape exits at football stadiums and planning for mass events.

As useful as it can be to assume that people are particles, most of know that we are a bit more complicated than that. Nanda Wijermans’ presentation on Friday the 18th of October at the Futures Institute, addressed this issue head on. She has set up a general framework for modeling crowds at, for example, concerts and bars. In her model, each individual has a set of rules governing how they respond to their memory and their physiological state. For example, if you have drunk a lot you might need to go to the toilet, or if you have lost your friends you might want to find them. These are all rules we can relate to from our own lives. These types of behavioural rules can reproduce some collective outcomes that we wouldn’t see in particles, such as people wandering off towards the toilet not because they need to wee but because they aimlessly follow a friend.

I can see how this could be a powerful tool for pub or bar designers who could run simulations to decide how to arrange the social space. Nanda herself is more interested in general questions about spontaneous emergence of social groupings. Much of the lively discussion during and after the seminar was about exactly what one can and cannot expect to achieve with more detailed models. In my view, if you are going to make a model more complicated then you need to address questions that can't be tackled with simpler models. There are certainly plenty such problems!

Nanda also presented her current research work at the Stockholm Resilience Centre, where she is now a Postdoc. Here she is applying agent-based models to questions of resource use and co-operation in irrigation systems in Bali. Her overall goal is to include realistic behaviour in modelling of our interactions with our environment.
This is a new blog on collective behavior and modeling by me, David Sumpter. I have also started a Twitter account.