Agent-Organized Networks for Dynamic Team Formation

Agent-Organized Networks for Dynamic Team Formation

Gaton, M.E. and desJardins, M., In Proceedings of AAMAS-2005, pp. 230-237. Agent-Organized Networks for Dynamic Team Formation Seo, Young-Woo Introduction Agent-Oriented Network (AON) An organizational network structure, or agent-to-agent interaction topology that is the result of local rewiring decisions made by the individual agents in a networked multi-agent

system. Goal of the individual agents: Increase the collective performance of the agent organization by rewiring of an initial (arbitrary) network topology instead of creating and removal of connections Strategy Design Issues Local estimation of global performance When/How to perform network adaptation (or rewiring) Effectiveness of a Strategy Learning rate, stability, global structure 2

Dynamic Multi-Agent Formation A Simple Model of Multi-Agent System Team of agents forms a structure (or a topology) on the fly in decentralized fashion Individual decision making is based on local information Tasks are generated periodically and broadcasted globally 3 A a1 ,..., a N , ki eij , uncommitted

a j A i 1, | | Tk : task RTk | Tk |~ U 1, M k : member of a team committed active si: States of an individual agent ai on the team formation -uncommitted: available, but not assigned to any task

-committed: assigned to a task, but the team works on the skill fulfillment on a task -active: the team is working on the task : interval between tasks : number time step of task advertisement : availability period of active agents 4 A valid team is a set of agents that induce a connected subgraph of the agent Social network and whose skill set fulfills the skill requirements for a given task. An uncommitted agent is only eligible to a task either initiate a team or

join a team 1 e I s , uncommitted ij IPi i a j A i e

ij 2 a j |Mk| Mk 5 Rewiring Strategies (1/2) Structure-based Preferential attachment

Rich-Get-Richer: A connectivity phenomenon observed in a scale-free network Probability of connecting to a given node in a network is proportional to that nodes degree P ai a j kj k l al N i2

6 Rewiring Strategies (2/2) Performance-based Consider the local performance and referral Rewire if the local performance is below the average of its immediate neighbors performance measures 1 Y ai ki Y a j a j A,eij 1

| valid team joined | Y a j | team joined | Disconnect from the neighbor that has the lowest performance Establish connection to neighbor with the highest performance by requesting referrals 7 Experiments Setting Random geographic graph Randomly placing N agents in the unit square and connecting two agents if they are within a predefined distance d

Actions of an individual agent Adapt the network / join teams Parameters N=100, = = = |T|=10, =2 8 | valid teams | TFP | tasks | 9 10

11 12

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