Reinforcement learning in Netlogo: Error: No urn specified - netlogo

Question

I'm totally new to NetLogo, and am trying to create an agent-based reinforcement learning (RL) model. I have recreated a toy model to get help on.
Here, one agent is doing RL by interacting with two agents, one of whom is unreliable (and so interactions with this agent ARE NOT reinforced), and another which is reliable (and so interactions with this agent ARE reinforced).
But I keep getting the error: Extension exception: No urn specified
So, clearly, I need to figure out how to specify urns!
The project folder is available for you to checkout at: http://bit.ly/1m8TAxq
Bellow is the minimal, complete, verify code is as follows (though you will need the URN extension in the linked dropbox folder above to do so).
Any help would be tremendously appreciated.
extensions [ urn ] ;; the urn extension that contains the RL functions
breed [ agents agent ]
globals [ ;; Global variables
A1 ;; urn-ball name of agent 1 (RED)
A2 ;; urn-ball name of agent 2 (GREEN)
]
agents-own [ ;; Values assigned to each agent
main-urn ;; Name of the Polya urn used in RL
interactionPartner ;; Variable tracking who the learner is interacting with
knowledgeState ;; Variable tracking whether the learner knows the truth after each interaction
]
to setup ;; Setup the stage
clear-all
reset-ticks
setup-agents ;; Sets up the agents
end
to have-agents-setup-urns ;; Setting up agent polya urns for reinforcement learning (by observer)
ask agent 0 [
set main-urn urn:make-polya-urn initial-weight (list A1 A2)
;; There are two types of balls in the urn: A1, A2 corresponding to the two possible agents with whom the chooser may interact
]
end
to setup-agents ;; Setting up the agents in the population (by observer)
create-agents 3 [
setxy (-6 * cos ( who * 360 / population-size)) (12 * sin (who * 360 / population-size))
set shape "circle"
set size 4
]
ask agent 0 [ ;; This is the agent doing the reinforcement learning (BLUE)
set color [0 0 255 175]
]
ask agent 1 [ ;; This is the unreliable agent (RED)
set knowledgeState 0
set color [255 0 0 175]
]
ask agent 2 [ ;; This is the reliable agent (GREEN)
set knowledgeState 1
set color [0 255 0 175]
]
end
to step ;; The step function
ask turtles [do-game-play]
tick
end
to go ;; The go function simply calls step continuously
step
end
to do-game-play ;; The game play function (by observer)
ask agent 0 [
set interactionPartner urn:draw-ball main-urn ;; Draw from the agent urn to figure out with whom to interact.
if (interactionPartner = A1) [
set knowledgeState ( 0 ) ;; If the interactionPartner is agent 1 (who is unreliable), then set agent 0 knowledge state to 0.
]
if (interactionPartner = A2) [
set knowledgeState ( 1 ) ;; If the interactionPartner is agent 2 (who is reliable), then set agent 0 knowledge state to 1, and reinforce.
urn:reinforce main-urn A2 1
]
]
end