Organization Design and
Dynamic Resources
Huzaifa Zafar
Computer Science Department
University of Massachusetts, Amherst
May 14, 2008
1
Organization Design

The organization of a multi-agent system is the
collection of roles, relationships, and authority structures
which govern its behavior - [Horling & Lesser 05]
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Organization Design v/s Operational Design
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Long Term v/s Short term
Used to guide
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Data Flow
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Resource Allocation
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Coordination Pattern
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… etc
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Dynamic Resources



Dynamic Resources are those resources where
some characteristics of the resource changes over
time
Example - Network Routing
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Cost of communication changes as network loads change
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Paths in multi-hop communication changes as links fail
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Environmental interference changes over time
Example 2 - Battery Power Consumption


More usage of power implies faster battery consumption
Less available power implies an agent can take up less
responsibility.
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Outline
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How can we make better use of resource allocation
given knowledge of the Organization design?
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Network Routing

eCQRouting
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Experimental Analysis
How can we redesign/adapt our organization to the
changing resource?
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Problem setup
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Challenges we face in solving this problem
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Example applications
May 14, 2008
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Motivation
Organization Knowledge, Message priority
Effect of message loss on performance
Agent A
Agent B
Application
Application
Application
Layer
Message
Layer
Application
Network
Message
Layer
Network
Layer
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Introduction
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Objectives:

Significant number of network exploration messages
required to support multi-hop communication



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In turn reduces available bandwidth for application messages
Reduce this number in order to increase application level
bandwidth
Further regulate the number of exploration messages based
on:

Priority of messages

Relationship between rate of message loss and performance
Use application level organizational estimates of
direction and priority of communication in network
level routing protocols
May 14, 2008
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Routing
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At each time step do:





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Each destination-agent sends out an exploration message
All other agents in the network receive this exploration
message and use the corresponding time delay to predict
cost of sending messages to the corresponding
destination
Agents develop policies for sending messages based on
costs
Policy dictates next hop when multi-hop routing
Cost of sending exploration messages?
eCQRouting: At each time step do:


Should I as the destination-agent send a message?
How much confidence do I as a source-agent have on the
policies?
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eCQRouting:
Organizational Input
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Direction and priority of communication

Effect of message loss on performance
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Minimum path-confidence
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Exploration-decision frequency
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Learning rate (α ) - For Q-Learing
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eCQRouting Step 1
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Each agent has access to a weighted graph
representing direction and priority of
communication between agent roles in the network
No network-level topological information
Use the graph to determine if an agent is a
destination-agent {Cluster-Head and RegionalAgents}.
All agents are source-agents
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Example Network
Sensor Agent
Regional Node
Exploration Messages
Cluster Head
Data Messages
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Exploration messages are sent along with Data messages, causing
interference and reduction in bandwidth
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eCQRouting Step 2.1:
source-agent
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Uses time delay in receiving exploration messages
along with Q-Learning to determine local policies


ConfidenceCurrent
represents
how
well
theexploration
Q-Value
Confidence
Time
ininQ-Value
receiving
messages
Learning
rate delay
reflects the current state of the network



The policy of an agent determines the next best hop to a
given destination
Confidence degrades with time in the absence of
exploration messages
Calculated at source:
The lower the confidence of an agent, the less its Q-Values
(and in turn policies) change with updates
May 14, 2008
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eCQRouting Step 2.2:
destination-agent
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Exploration

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Objective: Determine the cost of sending a message
from a source
Every cycle:

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
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Regulate this threshold depending on the organization (later
in this talk)
Confidence has dropped below a threshold
A minimum path-confidence threshold is provided
as input
Source agent communicates its confidence
Source-agents use exploration messages to
estimate time required to sending application
messages to the destination
May 14, 2008
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Example Network
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Benefits :



May 14, 2008
Lower number
of exploration
messages
Exploration
messages are of
a smaller size
Q-Table is
smaller
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eCQRouting Step 2.3:
Exploration based on message priority
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More frequent exploration by high priority
destinations (messages to the corresponding
destination have high priority)
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Destination agent changes threshold depending on
message priority
Q-Values of application messages to high priority
destinations are more accurate, with low priority
messages less accurate.
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eCQRouting Step 2.4:
Exploration based on message loss
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Source agents:
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Determine the rate of message loss to the destination
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Send message loss rate to the destination
Destination agents:
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Explore more frequently when current paths have
significant application-level performance degradation
Agents tolerate high message-loss rates if the
corresponding performance degradation is low
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eCQRouting Step 2.4 :
Exploration based on message loss
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CNAS
Collaborative Network for Atmospheric Sensing
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Power-Aware, Agent-Based nodes
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Hierarchical Organization
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Sensor Agents collect data

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Cluster Heads aggregate data and guide sensor
agents
Cluster Heads send aggregated data to regional
agents
May 14, 2008
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CASA -
Collaborative Adaptive Sensing of the Atmosphere
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Considerably higher bandwidth requirement than
CNAS
4 Roles; Radars, Feature Detectors, Feature
Repositories and Optimizers
Roles higher in the hierarchy communicate with
higher priority
May 14, 2008
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Experiment - Bandwidth
Increase
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Networks range from 4 agents to 100 agents
Agents are randomly placed such that density
remains constant as network size increases
1 Cluster Head for every 3 Sensor Agents; placed
randomly in the network
 35% additional
application
bandwidth in the
network of size
100 when
compared to OLSR
May 14, 2008
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Experiment - Robust
Performance
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Network of 160 agents
4 Optimizer agents; 4 FeatureRepository/Feature-Detector agents; Rest Radar
agents
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More robust
performance
degradation with
message loss
Insignificant difference
between the two
threshold modification
algorithms
May 14, 2008
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Conclusions
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Reduce network exploration messages

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Selected agents explore depending on organization
knowledge
Each agent explores only if the confidence in Q-Value of
the path is below a threshold
Regulate path-confidence threshold

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Priority of messages - high priority destinations explore
more often
Effect of message loss on performance - Significant
effect implies more exploration to find alternative paths
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Future Work - Problem Setup
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Resource - Network Routing
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Given - A basic organization
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Wireless Networks
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Agents enter and leave the network dynamically
Agent Failures
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Cost of sending messages fluctuate regularly
Adhoc Networks
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Question 1: How is this organization represented?
Agents are unable to communicate with their neighbors
Emergent Organization?
May 14, 2008
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Challenges
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Effect of change in organization on the network

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Goodness of Organization

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How do we determine if one organization is better than
another organization?
Cost of evaluating the organization

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Message interferences
Changes in costs with changes in traffic
Effects of mobility of nodes
Effect of time spent evaluating on the MAS
Reorganization/Adaptation costs
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Time spent in developing the new organization
Cost of updating all agents with the new organization
May 14, 2008
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Experimental Analysis
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Reorganizing CNAS
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Re-ordering the leader agent priority lists
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Regional nodes
RoboRescue
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Fire Hazards
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Organizing agents based on locations of fire hazards
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Predicting (or detecting) environmental changes
Communication Costs
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Reorganizing to reduce communication costs/limitations
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Questions and Discussion
May 14, 2008
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