19/10/2017 3:35pm
Our paper "Behaviour-Data Relations Modeling Language For Multi- #Robot Control Algorithms" now available to read!… [LINK]
18/10/2017 2:15pm
LEGO's new Women of NASA kit. Great learning for both kids and adults @LEGOIdeas [LINK] [LINK]
17/10/2017 11:01am
Nice open-call #reserch #fellowships programmes at LMU Munich [LINK]
16/10/2017 3:09pm
#robots that can merge and split their collective architecture (but the article title is preposterous @IEEESpectrum) [LINK]
13/10/2017 1:46pm
RT @MMGiuliani: First demo of our new human-robot interaction setup. Come visit us at @BristolRobotLab to have a look 😀. [LINK]

[Information Flow Principles in Robot Swarms]

Project: Designing Robot Swarms
Date: Oct 2015
Tags: swarm :: robotics :: C++

An important characteristic of a robot swarm operating in the real world is the ability to cope with changeable environments by exhibiting behavioral plasticity at the collective level. The word "plasticity" refers to the ability of a collective to respond to changes in the environment, without any help from humans.

For example, in the setting explored in our paper, we investigate how different robot algorithms work in environments where utility of resource deposits changes over time. An ideal system would always collect resources from a deposit with the highest utility. However, because robots need to cope with various problems and interferences, different algorithms achieve different performance.
Analyzing swarm behaviour in terms of information flow, a novel measure defined in our paper, can help us identify whether a particular robot control algorithm is likely to lead to plasticity of a swarm as a whole in dynamic environments.


Fast information flow is beneficial in static environments. Plastic swarm behaviour, important in dynamic or unknown environments, requires regulated information flow that leads to a greater balance between exploitation and exploration.

Swarm robotics, foraging, communication, self-organisation, plasticity

Publication: Pitonakova, L., Crowder, R. & Bullock, S. (2016). Information flow principles for plasticity in foraging robot swarms. Swarm Intelligence, 10(1), 33–63.

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