Mechanisms to Promote Cooperation in Decentralized Services

Outline System Model Cooperation Mechanisms Results Conclusions

Mechanisms to promote cooperationin decentralized services

E. del Val M. Rebollo V. Botti

Univ. Politecnica de Valencia (Spain)

EUMAS ’12Dublin, December 2012

M. Rebollo et al. (UPV) EUMAS’12Mechanisms to promote cooperation in decentralized services


Promoting Cooperation

MotivationThere are scenarios in decentralized systems in which cooperationplays a central role

agents connected in networksbounded rationalityheterogeneous, self-interested agents



Our Proposal

The challengeObtain an emergent, cooperative global behavior even whencooperators are a minority, from local decisions.

What is done. . .a network structure that ensures navigation and efficiencystructural changes to isolate undesired agentsincentives to promote cooperation



Outline

1 Outline

2 System Model

3 Cooperation Mechanisms

4 Results

5 Conclusions



System Model

Definition (Open Service-Oriented MAS)

(A, L), where A = {ai , ..., an} is a finite set of autonomous agentsthat are part of the system, and L ⊆ A× A is the set of links,where each link (ai , aj) ∈ L



System Model

Definition (Agent)

is a tuple (Si ,Ni , sti ) where:Si = {s1, . . . , sl} is the set of semantic service descriptions ofthe services provided by the agent (WSDL);Ni is the set of neighbors of the agent,Ni ⊆ A− {ai} : ∀aj ∈ Ni , ∃(ai , aj) ∈ L, and |Ni | > 0. It isassumed that |Ni | � |A|;sti is the internal state of the agent.πi : sti → Ni is the neighbor selection function thatdetermines the most promising neighbor to provide a service;ρi : sti → Ψ is the adaptation selection function where Ψ isthe set of finite adaptation actions of the agent.



Network Creation

probabilistic relations baed on homophily (assortativity,similarity)two agents are similar if they provide similar services

H = αHv + (1− α)Hs

growing network structure (exponential degree distribution)certain characteristics of a small-world network (short paths,clustering)



Service Discovery

navigation problem in networks (it relies in the agentcooperation)hill climbing (greedy) method

π(at) = argmaxaj∈Ni

1−1−

H(aj , at)∑an∈Ni

H(an, at)

|Nj |

agents pass the query until the desire service is foundit is a problem with self–interested agents



Social Plasticity

capacity to changerelations as times passeslink utility decays withtimedepends on the queries ajforwards

D(aj) = 11+e−γ



Social Plasticity

when an agent breaks a link, a substitute must be found(maintain the network structure)criteria

neighbor of neighbora similar agent to the previous one

rewire links has not a cost



Social Plasticity



Social Plasticity



Incentives

each action implies a cost (ask for a service and forward)a reward is obtained if the service is foundrewards are provided by the systemagents imitated the strategy of successful neighbors



Incentives



Combining social plasticity and incentives

Both strategies promote cooperation in generalbut it is not enough if non–cooperative agents has a highdegree

network broken in isolated partsrewire cost –> not affordable for some agentspayoff not enough to promote cooperation

the combined model1 incentives to change the behavior of non–cooperatives2 rewire links if it fails



Experiment Design

Configuration

1,000 agents, 10 different networks100 steps to forward a query, snapshots after 5,000 queriesvarying the initial prop. of collaborators

Strategies

Social plasticity (SP)IncentivesReinforcement Learning (RL) using WOLFGame-theory approach, using Prisoner’s Dilemma (PD)Incentives + Social Plasticity (I+SP)



Measures

proportion of collaborator / non–collaboratorsaverage path length (better if smaller)search failures due to non–collaborationsearch success (including TTL)



60% of collaborators (num and path length)



40% of collaborators (num and path length)



60% of collaborators (failures and success)



40% of collaborators (failures and success)



Conclusions

improving cooperation to solve navigation problem in networksapplied to decentralized service managementcombination of structural changes and incentivesimproves the performance when non-collaborators are’important’ in the networkworks by imitation: a core of collaborators is neededa guess: the size of the core depends on networkcharacteristics (percolation, efficience, centrality coefficient)


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Mechanisms to Promote Cooperation in Decentralized Services