Fighting noise with limited resources:

an ant colony perspective

Ofer FeinermanDept. of Physics of Complex Systems

Weizmann Institute of ScienceBiological Distributed Algorithms workshop

Colocated with DISC October 2013

The nuptial flight

Noise: Virgin queens differ in their sensitivity to heat/ light/humidity..

How do the ants avoid early activationby over-sensitive virgin queens?

Timeliness + Synchrony

Timing the nuptial flight

Negative + positive feedback: a collective mechanism for noise suppression.

Noise fighting rule: “Pull exiting virgin queens back into their nest.”

Introduction

Draw connections between:• Component characteristics (e.g. logical gates)• Component reliability• Circuit complexity• Circuit reliability

COMPUTER SCIENCE

Introduction -biologyAnts are small and biological and therefore inherently noisy.

Ant colonies show robust reactions to a changing environment.

The problems ants face are somewhat different than what was addressed in the 50’s:• Ants may have limitations but they are not logic gates• Ants do not function within a well structured network.

• Observe how real ants deal with the reliability problem.• Longer term goal lies in drawing connections similar to those

obtained in Computer Science.

Two collective behaviors

Desert ant, recruitment(published).

Crazy ant, collective load carrying(preliminary).

Desert ant recruitment

• Unlike previous example: no noise in sensing the environment.• Noisy communication. First recruitment attempt failed.

How can we explain this?Easy: a clear and distinguishable message that conveys recruitment.Minimal requirement: A two word (1 bit) vocabulary.

Recruitment performance

Ants recruit to food source and discriminate recruitment from other movements within nest

Quantifying communicationWe quantify communication indirectly by measuring the behavioral changethat is induced by interactions.

Quantifying communicationWe quantify communication indirectly by measuring the behavioral changethat is induced by interactions.

Technology is currently revolutionizing the field of collective animal behavior.

Obstacle: This requires a lot of interaction statistics!

+

Quantifying communicationWe quantify communication indirectly by measuring the behavioral changethat is induced by interactions.

Technology is currently revolutionizing the field of collective animal behavior.

+Repeating the experiment ~50 times gave us a database of 1000’s of interactions.

Obstacle: This requires a lot of interaction statistics!

Quantifying communicationWe quantify communication indirectly by measuring the behavioral changethat is induced by interactions.

Obstacle: What behavioral change should we look at?

Movement speed as a window into the ants’ inner states.

But: The probability that an ant exit the nest does NOT on whether she has recently (last 2 min) met a recruiter (P=0.46).

But: The speed of the ‘awakened’ ant does NOT depend on whether the other ant has been to the cricket (P=0.50).

Quantifying communicationWe quantify communication indirectly by measuring the behavioral changethat is induced by interactions.

Obstacle: What behavioral change should we look at?

Movement speed as a window into the ants’ inner states.

The probability that an ant leave the nest depends on her speed.An ant can gain in speed by meeting fast ants.

Quantifying information transfer: How sensitive is one ant to the other ant’s speed?

Information in interactions

and calculate the channel capacity.

ant 2 ant 1

11

00

Define an information channel:

Speed of ant 1before

interaction

Speed of ant 2 after

interaction

communication noise

1 bit

one input bit (fast/slow).

Experimentally:

binary channel

Information in interactions

and calculate the channel capacity.

ant 2 ant 1

11

00p

1-p

1-p

Define an information channel:

Speed of ant 1before

interaction

Speed of ant 2 after

interaction

communication noise

1 bit

0.22 bits = 1.2 words

one input bit (fast/slow).

Experimentally:

noisy binary channel

Collective reliability

Assertive• Move fast (interact often)• Do not adjust speed after interactions.

1st hand knowledge“confident”

2nd hand knowledge“unsure”

cric

ket

Hesitant• Slow down (limit your interactions)• Adjust speed after interactions.

Memory state Behavioral rules

To compensate for lack of reliable communication the ants rely on their memory and on simple interaction rules

From communication control to reliable group function

Fixed point analysis: • A nest in which no ant saw the cricket

will converge to fixed points of speed that are well under exit threshold.

• The persistent presence of a fast ant (the recruiter) pushes the fixed point towards the exit threshold.

Exit threshold

Speed modulation of non knowledgeable ants• Slow down (limit your interactions)

• Adjust speed after interactions.

The mechanism at workEarlynegative Feedback

A convicted ant overcomesnegative feedback

Recruitment Summary• Observe how real ants deal with the reliability problem.

• The further goal lies in drawing connections similar to those obtained in Computer Science.

Teaser: Could the ants perform as well with 0 bits of communication? At what cost?

Assess information Tune your influence

• Environmental info? Long lasting confidence

• Social info? Transient high speed

• Tune your interaction rate • Tune your response to interactions

Collective load carrying

Experimental setup

cm

Cheerio Trajectories

cm

Navigational trouble

• Carrying ants have trouble realizing the correct direction home.• Individual ants can make a positive difference.

Home Bound

Prominence of the updated

∑𝜏=0No Rotation

Prominence of the updated

∑𝜏 ≠0Rotation

∑𝜏=0No Rotation

Prominence of the updated

∑𝜏 ≠0Rotation

∑𝜏=0No Rotation

∑ 𝐹 ≠0Translation

∑ 𝐹=0No Translation

Prominence of the updated

Collective Carrying Summary• Observe how real ants deal with the reliability problem.

Ants tune their influence on collective direction in accordance to their information regarding the environment.

In a very literal way: knowledge is (pulling) power!

Suffering from noise?

Rely on first hand information.

rare noisy

Group: Both amplifies and limits the influence of this information.

ThanksAnt Lab• Nitzan Razin• Yael Heyman• Efrat Greenwald• Oded Shor• Ehud Fonio• Aviram Gelblum• Yuri Burnishev• Tal Eliav• Yuval Erez

• Jean-Pierre Eckmann (U. Geneve)

• Abraham Hefetz (TAU)• Amos Korman (Paris 7)

ISF Bikura, MINERVA Foundation, Clore Foundation