positional communication and private information in ... · what can we learn from biological models...
TRANSCRIPT
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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
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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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Peter Bailis - Harvard University 2010
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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Peter Bailis - Harvard University 2010
How Bees Communicate: Waggle Dance
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Peter Bailis - Harvard University 2010
How Bees Communicate: Waggle Dance
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Direction
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Peter Bailis - Harvard University 2010
How Bees Communicate: Waggle Dance
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Direction
Distance
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Peter Bailis - Harvard University 2010
How Bees Communicate: Waggle Dance
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Direction
Distance
Duration ~= Quality
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Peter Bailis - Harvard University 2010
Recent Controversy
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Peter Bailis - Harvard University 2010
Recent Controversy
5
Does the dance increase efficiency?
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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?
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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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Peter Bailis - Harvard University 2010
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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Peter Bailis - Harvard University 2010
Is sharing position information more useful than relying on private information, and when?
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Key Question
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Peter Bailis - Harvard University 2010
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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Peter Bailis - Harvard University 2010
Outline
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Motivation: Why bees and why foraging?
Design: Foraging model
Evaluation: Simulation and results
Discussion
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Peter Bailis - Harvard University 2010
Model
Goal: Accurately represent salient details of bee foraging as described in literature
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Peter Bailis - Harvard University 2010
World
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Hive
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Peter Bailis - Harvard University 2010
Food Distribution
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Flowers added at fixed rate
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Peter Bailis - Harvard University 2010
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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Peter Bailis - Harvard University 2010
Bee
Bee Model
• Inaccurate flight, limited energy and memory
Bee Roles
•Dynamic transitions
Shared versus Private Information
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Peter Bailis - Harvard University 2010
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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Peter Bailis - Harvard University 2010
Lévy Flight
16[Reynolds, Physics Letters A, 2006]
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Peter Bailis - Harvard University 2010
Role Transitions
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Dance Threshold
Forage Threshold
Qua
lity
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Peter Bailis - Harvard University 2010
Role Transitions
17
Dance Threshold
Forage Threshold
Qua
lity
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Peter Bailis - Harvard University 2010
Role Transitions
17
Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
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Peter Bailis - Harvard University 2010
Role Transitions
17
Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
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Peter Bailis - Harvard University 2010
Role Transitions
17
Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
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Peter Bailis - Harvard University 2010
Role Transitions
17
Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Continue to forage
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Peter Bailis - Harvard University 2010
Role Transitions
17
Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Continue to forage
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Peter Bailis - Harvard University 2010
Role Transitions
17
Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Continue to forage
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Peter Bailis - Harvard University 2010
Role Transitions
17
Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Continue to forage
Become unemployed
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Peter Bailis - Harvard University 2010
Role Transitions
17
Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Continue to forage
Become unemployed
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Peter Bailis - Harvard University 2010
Role Transitions
17
Dance Threshold
Forage Threshold
Advertise flower
Qua
lity
Continue to forage
Become unemployed
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Peter Bailis - Harvard University 2010
Role Transitions
17
Dance Threshold
Forage Threshold
Small probability of scouting
Advertise flower
Qua
lity
Continue to forage
Become unemployed
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Peter Bailis - Harvard University 2010
Communication Models
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Peter Bailis - Harvard University 2010
Communication Models
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SharePosition
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Peter Bailis - Harvard University 2010
Communication Models
18
SharePosition
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Peter Bailis - Harvard University 2010
Communication Models
18
SharePosition
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Peter Bailis - Harvard University 2010
Communication Models
18
SharePosition PrivatePosition
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Peter Bailis - Harvard University 2010
Communication Models
18
SharePosition PrivatePosition
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Peter Bailis - Harvard University 2010
Communication Models
18
SharePosition PrivatePosition
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Peter Bailis - Harvard University 2010
Communication Models
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SharePosition PrivatePosition
Previously encountered,
Privately remembered
sources
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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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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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Peter Bailis - Harvard University 2010
Outline
20
Motivation: Why bees and why foraging?
Design: Foraging model
Evaluation: Simulation and results
Discussion
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Peter Bailis - Harvard University 2010
Overall Efficiency
Efficiency metric:
Food gathered / Energy expended
Default comparison:
PrivatePosition to SharePosition
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Peter Bailis - Harvard University 2010
Overall Efficiency
22
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Peter Bailis - Harvard University 2010
Overall Efficiency
22
PrivatePosition better
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Peter Bailis - Harvard University 2010
Overall Efficiency
22
PrivatePosition better
SharePosition better
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Peter Bailis - Harvard University 2010
Overall Efficiency
22
Low (20 trips)Flower Capacities
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Peter Bailis - Harvard University 2010
Overall Efficiency
22
PrivatePosition can be more efficient than SharePosition!
Low (20 trips)Flower Capacities
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Peter Bailis - Harvard University 2010
Overall Efficiency
22
PrivatePosition can be more efficient than SharePosition!
Medium (60 trips)Low (20 trips)
Flower Capacities
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Peter Bailis - Harvard University 2010
Overall Efficiency
22
PrivatePosition can be more efficient than SharePosition!
Medium (60 trips)High (200 trips)
Low (20 trips)Flower Capacities
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Peter Bailis - Harvard University 2010
Overall Efficiency
22
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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Peter Bailis - Harvard University 2010
Relative performance depends heavily on environment
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Peter Bailis - Harvard University 2010
Known Food Sources
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Peter Bailis - Harvard University 2010
Known Food Sources
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PrivatePosition harvests from many more
sources
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Peter Bailis - Harvard University 2010
Known Food Sources
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PrivatePosition harvests from many more
sources
Capacity 20 trips
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Peter Bailis - Harvard University 2010
Oversubscription
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Peter Bailis - Harvard University 2010
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Peter Bailis - Harvard University 2010
Oversubscription
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Yum!
Yum!
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Peter Bailis - Harvard University 2010
Oversubscription
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Yum!
Yum!
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Peter Bailis - Harvard University 2010
Oversubscription
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Yum!
Yum!
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Peter Bailis - Harvard University 2010
Oversubscription
25
Yum!
Yum!
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Peter Bailis - Harvard University 2010
Oversubscription
25
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Peter Bailis - Harvard University 2010
Oversubscription
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(Potentially many) wasted trips!
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Peter Bailis - Harvard University 2010
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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Peter Bailis - Harvard University 2010
Unsuccessful Trips
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Peter Bailis - Harvard University 2010
Efficiency, Revisited
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Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
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Peter Bailis - Harvard University 2010
Efficiency, Revisited
28
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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Peter Bailis - Harvard University 2010
Clustered Efficiency
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Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
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Peter Bailis - Harvard University 2010
Clustered Efficiency
29
Efficiency again depends on
environment!
Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
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Peter Bailis - Harvard University 2010
Clustered Efficiency
29
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
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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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Peter Bailis - Harvard University 2010
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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Peter Bailis - Harvard University 2010
Heterogenous Worlds
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50% each quality
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Peter Bailis - Harvard University 2010
Efficiency
33
Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
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Peter Bailis - Harvard University 2010
Efficiency
33
SharePosition concentrates its efforts on fewer, but higher quality
sources
Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
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Peter Bailis - Harvard University 2010
Efficiency
34
Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
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Peter Bailis - Harvard University 2010
Efficiency
34
Again, SharePosition is
better in heterogenous
worlds...
Low (20 trips)Medium (60 trips)High (200 trips)
Flower Capacities
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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
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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?
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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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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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Peter Bailis - Harvard University 2010 43