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Weekly Project Dashboard: Project Name: EGT for Mobile Ad Hoc Networks Name: Jeffrey Hudack Date: 4/20/2012. G. Key Accomplishments for this Reporting Period ICAART 2013 paper updated Example figure for cooperation clustering - PowerPoint PPT Presentation
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Weekly Project Dashboard:Project Name: EGT for Mobile Ad Hoc NetworksName: Jeffrey Hudack Date: 4/20/2012
GKey Accomplishments for this Reporting Period
ICAART 2013 paper updated Example figure for cooperation clustering Motivation for RGG model
Investigated extensions for next paper IPD assumes memory and identity If strategies are exclusive to a single other agent then there’s almost no spatial influence Random Flooding is a common method for packets transfer in MANETs that change often
Key Accomplishments for this Reporting Period
ICAART 2013 paper updated Example figure for cooperation clustering Motivation for RGG model
Investigated extensions for next paper IPD assumes memory and identity If strategies are exclusive to a single other agent then there’s almost no spatial influence Random Flooding is a common method for packets transfer in MANETs that change often
Check Points & Milestones Status Start Fcst.EndSPD Draft to Dr. Oh and PA Complete 6/25ICAART 2013 Green 5/9 7/24AMAAS 2013 Red 6/22 10/8EGT Background Green 5/28 Oct 2012Proposal Defense Spring 2013Dissertation Defense Fall 2013
Check Points & Milestones Status Start Fcst.EndSPD Draft to Dr. Oh and PA Complete 6/25ICAART 2013 Green 5/9 7/24AMAAS 2013 Red 6/22 10/8EGT Background Green 5/28 Oct 2012Proposal Defense Spring 2013Dissertation Defense Fall 2013
Research IssuesThe effects of changing networks on repeated interactions between agentsConvergence of cooperation in populations with dynamic interaction based on various mobility modelsCharacterizing the rate of change of the network as a function of number of moving agents, the density of the agents, the movement model, and their velocity
Research IssuesThe effects of changing networks on repeated interactions between agentsConvergence of cooperation in populations with dynamic interaction based on various mobility modelsCharacterizing the rate of change of the network as a function of number of moving agents, the density of the agents, the movement model, and their velocity
Plans for Next Reporting Period
•Plan path for next publication• Iterated games• Stochastic game theory• Alternative replicator dynamic
•Increasing complexity•Anonymous Packets•ID of packet requestor known•ID of packet originator known•With noise
•Mis-play (node error) chance•Mis-read (sensing error) chance
Plans for Next Reporting Period
•Plan path for next publication• Iterated games• Stochastic game theory• Alternative replicator dynamic
•Increasing complexity•Anonymous Packets•ID of packet requestor known•ID of packet originator known•With noise
•Mis-play (node error) chance•Mis-read (sensing error) chance
Plans Beyond Next Reporting Period
Combine the mobility model for spatial PD with graph theoretic methods for connectivity and disruption of ad hoc networks
Develop disruptive agent “teams” with squad-based movement models to characterize how ad hoc networks could be disrupted when the nodes adopt the PD mechanism for promoting cooperation
Plans Beyond Next Reporting Period
Combine the mobility model for spatial PD with graph theoretic methods for connectivity and disruption of ad hoc networks
Develop disruptive agent “teams” with squad-based movement models to characterize how ad hoc networks could be disrupted when the nodes adopt the PD mechanism for promoting cooperation