Do you mean "how cooperation is emerged" or "how cooperation generates emergence"?

Rather the first - can cooperation emerge in an interaction network of embodied agents (examining different kind of topologies: scale-free, small world etc.)? and can it resist threats.

You might be interested in S.T.Shutters, "Punishment Leads to Cooperative Behavior in Structured Societies", Evolutionary Computation Summer 2012, Vol. 20, No. 2: 301–319. In this work, simulated agents interact according to one of several kinds of social network structure (eg small-world, Moore or scale-free) and play a continuous version of Prisoner's Dilemma against each other. For each encounter, some adjacent third party can punish insufficient co-operation, but at a cost to the punisher.

Co-operation emerges and is stable for most sorts of social network, although not for scale-free networks. I have done some further work on that to investigate why. It seems that in scale-free networks there are enough paths that act as delay lines for the spread of different strategies, so that strategy oscillation can happen and can persist.

Thanks for the pointers.

I would add Robert Axelrod works : http://www-personal.umich.edu/~axe/research_papers.html whose researches deal with iterated prisoner's dilemma, showing how collaboration can emerge in a network of agents playing this game.

Thanks. I am aware of that work but am particularly looking for work that covers embodied agents

I have a publication in press at the _IEEE Transactions on Cybernetics_ that may be of interest. Here's a pre-print:

http://pubs.tedpavlic.com/PavlicPassino13.pdf

Here's the title:

Distributed and Cooperative Task Processing: Cournot Oligopolies on a Graph

by Theodore P. Pavlic and Kevin M. Passino

Target applications include autonomous air vehicles, but the framework is general and abstract. In the end, the network topology coupled with local incentive structures is what makes the non-trivial cooperation strategies emerge.

One of the sufficient conditions for stability is what appears to be another network-generalization of Hamilton's rule, FYI.

And if you're interested in self-organized behavior in general, there are lots of robotics papers on that. We have another paper just submitted to ISRR on a stochastic allocation strategy for mobile robots that produces stable and predictable team sizes around loads although there is no (conventional) communication between robots. If that paper gets accepted, I'd be happy to attach a pre-print.

This PhD thesis elaborates on the emergence of cooperation via specialization and organization of different roles and tasks. The researchers applied a threshold adaptation mechanism to a robotic swarm in which each individual is controlled via a spiking neural network. They also developed a software framework to simulate these behaviors in a robot swarm.

http://archivia.unict.it/bitstream/10761/1310/1/VTNLSN83H70C351Q-AVitanza1.pdf

Ok - thanks.

Regarding the robotics part, you could check our literature survey if you want: http://link.springer.com/article/10.1007%2Fs11721-012-0075-2

try these:

Gabora, L. (2013). An evolutionary framework for culture: Selectionism versus communal exchange. Physics of Life Reviews, 10(2), 117-145. [pdf]

Gabora, L. (2013). Reply to the commentaries on “An evolutionary framework for cultural change: Selectionism versus communal exchange”. Physics of Life Reviews, 10(2), 162-167. [pdf]

Gabora, L. (in press). Cultural evolution as distributed human computation. In P. Michelucci (Ed.) Handbook of Human Computation. Springer.

Gabora, L., & Ranjan, A. (2013). How insight emerges in distributed, content-addressable memory. In A. Bristol, O. Vartanian, & J. Kaufman (Eds.) The neuroscience of creativity. New York: MIT Press. [pdf]

Gabora, L., & Kitto, K. (2013). Concept combination and the origins of complex cognition. In (E. Swan, Ed.) Origins of mind: Biosemiotics Series, Vol. 8 (pp. 361-382). Berlin: Springer. [pdf]

I have a couple of related publications:

H. Franks, N. Griffiths, and S. S. Anand, Learning Influence in Complex Social Networks, in Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013), pp. 447-454, 2013.

H. Franks, N. Griffiths and A. Jhumka, Manipulating Convention Emergence using Influencer Agents, Journal of Autonomous Agents and Multi-Agent Systems, 26(3) pp. 315-353, 2013 (doi:10.1007/s10458-012-9193-x).

(There are more on my webpage if you are interested - http://www.dcs.warwick.ac.uk/~nathan/publications/publications.html - I've yet to add all my publications to Research Gate!)

A little bit about a reported phonemena, may lead to a good model for agents as well.

Farenzena, D. S. et tal. "Collaboration Emergence in Social Networks with Informational Natural Selection"

I just read a paper called "Emergent Phenomena Belonging only to Biology" by Hugues Bersini (Synthesis, 2012, 185:257-272). In this paper he mentions the European Swarm Bot project coordinated in his laboratory (see beginning of section 2) which seems to be very much related to what you are looking for.

I'm sorry for the delay. Here is the link for the paper: http://atlanta.inf.ufrgs.br/lab/Content/paper/collaboration-emergence-social-preprint.pdf

We already performed experiments to complement the results and provide new explanations for the phenomena, but the article is still under development. You can follow our projects from here: http://atlanta.inf.ufrgs.br/lab/

Ok thanks.

The Swarmbot research project conducted by Marco Dorigo and his collaborators unveiled very interesting results that reflect the dynamics of collective systems. The technical report below is about distributed decision making from a swarm intelligence perspective.

Conference Paper Emergent collective decisions in a swarm of robots