"This work is devoted to communication approaches, which spread information in robot swarms. These mechanisms are useful for large-scale systems and also for such cases when a limited communication equipment does not allow routing of information packages. We focus on two approaches such as virtual fields and epidemic algorithms, discuss several aspects of hardware implementation and demonstrate experiments performed with microrobots "Jasmine"."

"Recent years are seeing an increasing need for on-line monitoring of teams of cooperating agents, e.g., for visualization, or performance tracking. However, in monitoring deployed teams, we often cannot rely on the agents to always communicate their state to the monitoring system. This paper presents a non-intrusive approach to monitoring by 'overhearing', where the monitored team's state is inferred (via plan-recognition) from team-members' routine communications, exchanged as part of their coordinated task execution, and observed (overheard) by the monitoring system. Key challenges in this approach include the demanding run-time requirements of monitoring, the scarceness of observations (increasing monitoring uncertainty), and the need to scale-up monitoring to address potentially large teams. To address these, we present a set of complementary novel techniques, exploiting knowledge of the social structures and procedures in the monitored team: (i) an efficient probabilistic plan-recognition algorithm, well-suited for processing communications as observations; (ii) an approach to exploiting knowledge of the team's social behavior to predict future observations during execution (reducing monitoring uncertainty); and (iii) monitoring algorithms that trade expressivity for scalability, representing only certain useful monitoring hypotheses, but allowing for any number of agents and their different activities to be represented in a single coherent entity. We present an empirical evaluation of these techniques, in combination and apart, in monitoring a deployed team of agents, running on machines physically distributed across the country, and engaged in complex, dynamic task execution. We also compare the performance of these techniques to human expert and novice monitors, and show that the techniques presented are capable of monitoring at human-expert levels, despite the difficulty of the task."

"We study equilibrium configurations of swarming biological organisms subject to exogenous and pairwise endogenous forces. Beginning with a discrete dynamical model, we derive a variational description of the corresponding continuum population density. Equilibrium solutions are extrema of an energy functional, and satisfy a Fredholm integral equation. We find conditions for the extrema to be local minimizers, global minimizers, and minimizers with respect to infinitesimal Lagrangian displacements of mass. In one spatial dimension, for a variety of exogenous forces, endogenous forces, and domain configurations, we find exact analytical expressions for the equilibria.…"

"Most of Gowers recommendations seem to focus on alignment and cohesion, but point 8, for example, is about separation: one member should not jump onto another's idea with a full proof until there is group support for that. It would be worthwhile to examine the list in detail from the perspective of the three rules of flocking, I bet."

"The idea builds on an installation, called Bacterial Orchestra, the pair took in 2006 to Brazil, Germany, Norway and elsewhere. This year, the new generation, called Public Epidemic No.1 is spreading beyond the microphones and loudspeakers of the original installation.

Cornéer said the current project could be hosted on any mobile phone but they chose the iPhone “because it’s popular and the centralized App Store makes it easy for the epidemic to spread.”

Check out the clip from the first test of the project above and follow after the jump for more detail on how it works."

"The systems we keep will be hybrid creations. They will have a strong rootstock of peer-to-peer generation, grafted below highly refined strains of controlling functions."