L ECTURE 24: S WARM I NTELLIGENCE 5 / A NT C OLONY O PTIMIZATION 1 T - - PowerPoint PPT Presentation
15-382 C OLLECTIVE I NTELLIGENCE - S19 L ECTURE 24: S WARM I NTELLIGENCE 5 / A NT C OLONY O PTIMIZATION 1 T EACHER : G IANNI A. D I C ARO M U LT I - A G E N T ( O P T I M I Z AT I O N ) S T R AT E G I E S What are the capabilities of the
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Problem / Physical Neighborhood Topological / Social Communication / Cooperation Neighborhood
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S O L U T I O N C O N S T R U C T I O N M E TA H E U R I S T I C ( S I N G L E A G E N T )
Backtracking: A remove_from_solution() function can be also used to remove variables (and possibly to assign them a different value in a next step) during the construction process (e.g., to repair infeasibility)
Knapsack TSP
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✦ Stigmergy is at the core of most of all the amazing collective
behaviors exhibited by the ant/termite colonies (nest building, division of labor, structure formation, cooperative transport)
✦ P
. Grassé (1959) introduced the term to explain nest building in termite societies (from the Greek stigma: sting and ergon: work, incite to work!): A stimulating configuration triggers a building action of a termite worker, transforming the configuration into another configuration that may trigger in turn another (possibly different) action by the same or other termites.
Guy Theraulaz and Eric Bonabeau. 1999. A brief history of stigmergy. Artificial Life 5(2), 97-116.
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✦ Stigmergy: any form of indirect communication among a set of (possibly)
concurrent and distributed agents which happens through acts of local modification of the environment and local sensing of the outcomes of these modifications Best analogy: Blackboard/Post-it style
communications
✦ Stigmergic variables: The local environment’s
variables whose value determine in turn the characteristics of agents’ response
✦ The presence of stigmergic variables is
“expected” (depending on parameter setting) to give raise to self-organized global behaviors or structural patterns (e.g., nest building, chaining) Stigmergic communication and control mechanisms in social insects have been reverse engineered to give raise to a multitude of ant (colony) inspired algorithms
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✦ Stigmergy leading to diverging group behavior: each agent has a different
threshold to respond to the presence and the value of a stigmergic variable
✦ Distribution of labor ✦ Automatic task allocation ✦ Specialization of work
clustering of objects (Bonabeau et al., 1997, Lumer and Faieta, 1994)
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✦ Stigmergy leading to converging group behavior: the majority of the agents
converge performing the same task or showing the same behavior
✦ Stigmergic variable: Intensity of pheromone trails in ant foraging →
Convergence of the colony on the shortest path between the nest and sources of food (Goss, Aron, Deneubourg, and Pasteels, 1989)
✦ While walking or touching objects, ants release a
volatile chemical substance, called pheromone
✦ Pheromone distribution modifies the environment (the
way it is perceived by other ants) creating a sort of attractive potential field for the ants
π ( τ η) ,
π τ η
Decision Rule Stochastic Morphology Terrain Pheromone
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Retracing the way back Mass recruitment Labor division Find shortest paths Communicate alerts
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✦ Use of ant colony inspire pheromone-based shortest path finding is at the core of
the work of the Ant Colony Optimization metaheuristic
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✦ Binary bridge with equal branches (Denebourg et al., 1990)
Upper Branch Nest Food 15 cm Lower Branch
20 40 60 80 100 5 10 15 20 25 30 % of passages Time (minutes) Upper branch Lower branch
pheromone deposit on the branch → Attraction towards the branch
Forward Backward
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Nest Food
t = 0 t = 1
Nest Food Food Nest
t = 2 t = 3
Nest Food
Pheromone Intensity Scale
#Pheromone on a branch ∝ Frequency of fw/bw crossing ∝ Length (quality) of paths