Multiagent Systems

Ants seem to be popular lately. There is a new podcast on ants from Russ Roberts at econtalk where he interviews Deborah M Gordon on her book Ants at Work.

I first note how suboptimal the ants behavior can be. As she points out, foraging ants will actually walk over large piles of food in order to get to the original food source they had found in the day. In fact, they will continue to do this all day simply because it is not the forager's job to find food, it is the scout's and the scouts only go out earlier in the morning. Note also that it is the same ants who can play the role of either forager or scouts.

This inefficiency should not come as a surprise when we realize that ants evolved their fixed behaviors to survive in a very specific world, one where food evenly distributed over the landscape and large piles of food do not appear out of nowhere. Still, it should serve as a warning to anyone who thinks of building biologically-inspired multiagent systems. Similarly, anyone who thinks that a system is robust simply because it is "bio-inspired" is mistaken.

Russ and Deborah also had a discussion on the differences between the emergence in ants and in the economy. Namely, ants are hardwired to some very specific very simple behaviors while people are autonomous intelligent selfish agents. I note that most multiagent systems must lie somewhere between these two extremes. The simple behaviors of ants are rarely sufficient to get the job done while, at the other end, no one has yet built a generally intelligent agent. The question we face is: do I solve this bit of the problem with a simple clever behavior or do I have to increase the complexity of the agents?