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I agree that Netlogo is a useful tool for exploring emergence because it allows us to create a world and a bunch of agents that can do interesting things, but I still think that using models to explore the capabilities that we listed will get increasingly challenging the more we move down the following list of what agents need to do:

• move, with some degree of randomness
• observe, interact with world
• learn from interactions with world
• get it less wrong - induction
• create internal models of the world
• think - deduction, abduction
• evolve, from inanimate to animate to story tellers?

I guess we will just have to start out simple and go from there, switching things and playing with the codes. AS far as the reading for this week, I enjoyed reading “From Complexity to Emergence and Beyond” again because it sort of highlighted a lot of the questions that we have been discussing during the semester such as the underlying principles of emergence as well as different examples of this phenomenon. I think that the distinction between strong and weak emergence made a lot more sense now that I have a greater understanding of emergence deterministic vs. non-deterministic systems.

We talked about evolution and in our last class and I agree that while randomness is a driving force of evolution, evolution is a driving force for the complexity and diversity that is present in nature. I found an interesting paper about the top questions of emergence (http://arxiv.org/ftp/nlin/papers/0509/0509049.pdf), and one of the questions that is discussed in the paper is about the relation between emergence and evolution. Are there any processes similar or related to ‘emergence” in evolution? The paper mentions that sudden jumps in complexity due to evolution are often related to fitness barriers. I know that in our last class we briefly talked about barriers and how that can affect how an entity observes and interacts with the world and this is something that we observed very early on in the course using Langton’s Ant model. According to the paper, there are at least three difference ways to cope with fitness barriers:

1)      to wait for a catastrophe, until the barrier is reduced through catastrophic events

2)      to bypass through exaptation (a process in which a feature acquires a function that was not acquired through natural selection): explore a different direction and make a sudden side lap

3)      to tunnel right through the barrier by burrowing complexity

The paper did not mention more on evolution and emergence…I’m interested in what else we can say about emergence and evolution…especially after we continue exploring models using netlogo…