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Positional Communication and Private Information in Honeybee Foraging Models
Peter Bailis, Radhika Nagpal, and Justin Werfel
HarvardSchool of Engineeringand Applied Sciences
ANTS 2010: September 8, 2010
Peter Bailis - Harvard University 2010
Harvard RoboBees ProjectGoal: Build swarms of micro-robotic insect pollinators
What tradeoffs do we need to make between complexity and performance?
What can we learn from biological models about bee behavior?
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Collective Honeybee BehaviorHoneybee colonies exhibit amazing collective behavior
• Large-scale (20-30K), decentralized multi-agent coordination using extremely simple mechanisms
• Foraging: dynamic task allocation across changing environments (bees to known sources)
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How Bees Communicate: Waggle Dance
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How Bees Communicate: Waggle Dance
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Direction
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How Bees Communicate: Waggle Dance
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Direction
Distance
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How Bees Communicate: Waggle Dance
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Direction
Distance
Duration ~= Quality
Peter Bailis - Harvard University 2010
Recent Controversy
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Recent Controversy
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Does the dance increase efficiency?
Peter Bailis - Harvard University 2010
Recent Controversy
Recent study: 93% of foragers studied relied on private information about food sources instead of following a dance’s cues [Grüter et al., 2008, Proc. R. Soc. Lond. B Biol.]
Lack of location information often does not affect colony success [Sherman and Visscher, 2002, Nature]
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Does the dance increase efficiency?
Peter Bailis - Harvard University 2010
Recent Controversy
Recent study: 93% of foragers studied relied on private information about food sources instead of following a dance’s cues [Grüter et al., 2008, Proc. R. Soc. Lond. B Biol.]
Lack of location information often does not affect colony success [Sherman and Visscher, 2002, Nature]
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New theory: shared information is a backup for private information [Grüter and Farina, March 2009, Trends in Ecology and Evolution]
Does the dance increase efficiency?
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Critical response: results are inconclusive [Brockmann and Sen Sarma, November 2009, Trends in Ecology and Evolution]:
“...there has not been a rigorous analysis to date of how to assess correctly the efficiency of the dance language or any other symbolic system that communicates spatial information”
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Is sharing position information more useful than relying on private information, and when?
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Key Question
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Key Variables
We explore the effect of the food’s
•Distribution: Clustered or scattered
•Density: Many or few food sources
•Quality: Homogeneous or heterogeneous
•Quantity: Amount of food per source
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Outline
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Motivation: Why bees and why foraging?
Design: Foraging model
Evaluation: Simulation and results
Discussion
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Model
Goal: Accurately represent salient details of bee foraging as described in literature
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World
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Hive
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Food Distribution
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Flowers added at fixed rate
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Flower Quality
Capacity: fixed number of visits
Nectar value: 1 or 4 sugar units per visit [Dornhaus et. al., Behavioral Ecology and Sociobiology, 2006]
Overall flower quality metric:
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(Distance from Hive)
(Maximum Distance)(Nectar Value)*(1- )
[Seeley, Wisdom of the Hive, 1996]
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Bee
Bee Model
• Inaccurate flight, limited energy and memory
Bee Roles
•Dynamic transitions
Shared versus Private Information
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Bee Roles
Scout: look for new food sources, remember best one
Forager: move to and collect food from known source; if known source not present, search for replacement
Unemployed: no known food source, wait in hive to be recruited
[Similar to de Vries and Biesmeijer, Behavioral Ecology and Sociobiology, 1998, and others]
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Lévy Flight
16[Reynolds, Physics Letters A, 2006]
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Role Transitions
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Dance Threshold
Forage Threshold
Qua
lity
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Role Transitions
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Dance Threshold
Forage Threshold
Qua
lity
Peter Bailis - Harvard University 2010
Role Transitions
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Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Peter Bailis - Harvard University 2010
Role Transitions
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Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Peter Bailis - Harvard University 2010
Role Transitions
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Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Peter Bailis - Harvard University 2010
Role Transitions
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Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Continue to forage
Peter Bailis - Harvard University 2010
Role Transitions
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Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Continue to forage
Peter Bailis - Harvard University 2010
Role Transitions
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Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Continue to forage
Peter Bailis - Harvard University 2010
Role Transitions
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Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Continue to forage
Become unemployed
Peter Bailis - Harvard University 2010
Role Transitions
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Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Continue to forage
Become unemployed
Peter Bailis - Harvard University 2010
Role Transitions
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Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Continue to forage
Become unemployed
Peter Bailis - Harvard University 2010
Role Transitions
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Dance Threshold
Forage Threshold
Small probability of scouting
Advertise flower
Qua
lity
Continue to forage
Become unemployed
Peter Bailis - Harvard University 2010
Communication Models
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Peter Bailis - Harvard University 2010
Communication Models
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SharePosition
Peter Bailis - Harvard University 2010
Communication Models
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SharePosition
Peter Bailis - Harvard University 2010
Communication Models
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SharePosition
Peter Bailis - Harvard University 2010
Communication Models
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SharePosition PrivatePosition
Peter Bailis - Harvard University 2010
Communication Models
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SharePosition PrivatePosition
Peter Bailis - Harvard University 2010
Communication Models
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SharePosition PrivatePosition
Peter Bailis - Harvard University 2010
Communication Models
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SharePosition PrivatePosition
Previously encountered,
Privately remembered
sources
Peter Bailis - Harvard University 2010
Communication Models
SharePosition: Recruits forage at location specified by dance
PrivatePosition: Recruits forage at previously known location, or, if they have none, become scouts
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Peter Bailis - Harvard University 2010
Communication Models
SharePosition: Recruits forage at location specified by dance
PrivatePosition: Recruits forage at previously known location, or, if they have none, become scouts
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Two extremes
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Outline
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Motivation: Why bees and why foraging?
Design: Foraging model
Evaluation: Simulation and results
Discussion
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Overall Efficiency
Efficiency metric:
Food gathered / Energy expended
Default comparison:
PrivatePosition to SharePosition
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Overall Efficiency
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Overall Efficiency
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PrivatePosition better
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Overall Efficiency
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PrivatePosition better
SharePosition better
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Overall Efficiency
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Low (20 trips)Flower Capacities
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Overall Efficiency
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PrivatePosition can be more efficient than SharePosition!
Low (20 trips)Flower Capacities
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Overall Efficiency
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PrivatePosition can be more efficient than SharePosition!
Medium (60 trips)Low (20 trips)
Flower Capacities
Peter Bailis - Harvard University 2010
Overall Efficiency
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PrivatePosition can be more efficient than SharePosition!
Medium (60 trips)High (200 trips)
Low (20 trips)Flower Capacities
Peter Bailis - Harvard University 2010
Overall Efficiency
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PrivatePosition can be more efficient than SharePosition!
Medium (60 trips)High (200 trips)
Low (20 trips)Flower Capacities
...but isn’t always more
efficient!
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Relative performance depends heavily on environment
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Known Food Sources
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Known Food Sources
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PrivatePosition harvests from many more
sources
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Known Food Sources
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PrivatePosition harvests from many more
sources
Capacity 20 trips
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Oversubscription
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Oversubscription
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Oversubscription
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Yum!
Yum!
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Oversubscription
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Yum!
Yum!
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Oversubscription
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Yum!
Yum!
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Oversubscription
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Yum!
Yum!
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Oversubscription
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Oversubscription
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(Potentially many) wasted trips!
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Foraging at more food sources results in greater diversity in forager allocation
• Low capacities result in high oversubscription--more wasted trips!
•With higher capacities, oversubscription costs are amortized across more trips
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Unsuccessful Trips
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Efficiency, Revisited
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Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
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Efficiency, Revisited
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As generation rates increase,
chance of finding replacement flower after depletion
Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
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Clustered Efficiency
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Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
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Clustered Efficiency
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Efficiency again depends on
environment!
Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
Peter Bailis - Harvard University 2010
Clustered Efficiency
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In clustered world, harder to find additional flower once
cluster is depleted
Efficiency again depends on
environment!
Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
Peter Bailis - Harvard University 2010
Observation: under this model, clusters are essentially super-food sources
•Depletion and recovery speeds determined by flower generation rate
Clustered world is analogous to having ten super-flowers; location matters
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PrivatePosition’s successes are due to its diversity of sources
• Reduces oversubscription problem
•With higher amounts of food, and when food is easy to find or geographically correlated, less advantageous
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Heterogenous Worlds
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50% each quality
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Efficiency
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Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
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Efficiency
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SharePosition concentrates its efforts on fewer, but higher quality
sources
Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
Peter Bailis - Harvard University 2010
Efficiency
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Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
Peter Bailis - Harvard University 2010
Efficiency
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Again, SharePosition is
better in heterogenous
worlds...
Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
Peter Bailis - Harvard University 2010
Summary
PrivatePosition is better in worlds with:
• Fast source depletion
•Many easy-to-find sources
SharePosition is better in worlds with:
• Low risk of oversubscribing sources
•Heterogeneous source qualities
• Few hard-to-find sources
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Peter Bailis - Harvard University 2010
Outline
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Motivation: Why bees and why foraging?
Design: Foraging model
Evaluation: Simulation and results
Discussion
Peter Bailis - Harvard University 2010
Discussion
Effectiveness depends on a careful balance between
having a diversity of food sources, decreasing the risk of oversubscribing them and wasting energy and
concentrating efforts on the best sources
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Peter Bailis - Harvard University 2010
Discussion
However, PrivatePosition can outperform SharePosition by over 35%
This supports Grüter’s hypothesis regarding the role of private information in forager allocation
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Peter Bailis - Harvard University 2010
RoboBees
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•Open Questions:
•How complex do agents need to be?
•What communication capabilities are necessary?
Peter Bailis - Harvard University 2010
Conclusion
Relying on private information in bee foraging can be advantageous in several environment types due to an increased diversity in food sources
• This supports recent claims about the role of the waggle dance and private information
• Relative efficiency dependent on many environmental factors
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Peter Bailis - Harvard University 2010
Thank YouData and open source (GPL) code:
http://eecs.harvard.edu/~pbailis/beesim/
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Peter Bailis - Harvard University 2010
Conclusion
Relying on private information in bee foraging can be advantageous in several environment types due to an increased diversity in food sources
• This supports recent claims about the role of the waggle dance and private information
• Relative efficiency dependent on many environmental factors
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