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Chapter 8:
Multi-agents
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Objectives
• List and describe the dimensions of a multi-agent system:
heterogeneity, control regime, cooperation, and goals
• List and describe the axes for describing a MAS task (time, subject
of action, movement, dependency)
• List and describe the axes for describing a MAS collective
(composition, size, communications, reconfigurability)
• Compute the social entropy of a team.
• Describe the use of social rules and internal motivation for
emergent social behavior.
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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The Study of Multiple Robots
Distributed
Artificial
Intelligence
Distributed
Problem
Solving
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
MultiAgent
Systems
Chapter 8: Multi-agents
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The Study of Agency
(after Stone and Veloso 2002)
Distributed
Artificial
Intelligence
Distributed
Problem
Solving
Single computer:
•How to decompose task?
•How to synthesize solutions?
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
How to solve problems
Or meet goals by
“divide and conquer”
MultiAgent
Systems
Divide among agents:
•Who to subcontract to?
•How do they cooperate?
Chapter 8: Multi-agents
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4 Dimensions of a
Multi-agent System
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• Heterogeneity
– Same (homogeneous) vs. different (heterogeneous)
– Can be different on either software or hardware
• Control Regime
– Centralized vs. Distributed
• Cooperation
– Active (acknowledge each other) vs. Non-active (cooperation
emerges, not explicit)
– Communicating or non-communicating
• Goals
– Common goal (same, explicit) vs. Individual goal
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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The Ecological Niche of a MultiAgent System
Remember….
• Single Robot
– Task
– Environment
– Agent
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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The Ecological Niche of a MultiAgent System
• Multi-agent system
– Task
– Environment
– Individual Agent
– Collective
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
emphasis
Chapter 8: Multi-agents
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3 Categories of Dependency
1. Independent
– Robots don’t have to work directly or be aware of
others
2. Dependent
– Must work together for efficiency ex. Box pushing
3. Interdependent
– Cyclic dependency ex. resupply
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Box-Pushing
Chapter 8: Multi-agents
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MAS Task Summary
• Time
–
–
–
–
Fixed time task (ex. Collect as many cans in 10 minutes)
Minimum time (ex. Visit all rooms as fast as possible)
Unlimited time (ex. Patrol the building)
Synchronization required (ex. Push two buttons at same time)
• Subject of Action
– Object-based (e.g., robots place a single object- soccer)
– Robot-based (e.g., robots place themselves- mapping)
• Movement
–
–
–
–
Coverage (ex. Spread out to cover as much as possible)
Convergence (ex. Robots meet from different start positions)
Movement-to (ex. Going to a single location)
Movement-while (ex. Formation control)
• Dependency
– Independent (ex. Doesn’t require agents to know about others)
– Dependent (ex. Task requires multiple agents)
– Interdependent (ex. Agents depend on each other cyclically)
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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2 Categories of Composition
• Composition
– Homogeneous
– Heterogeneous
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Case Studies
• Georgia Tech 1994 AAAI
Mobile Robot Competition
team
• Each robot hardware and
software homogeneous
• Reactive behaviors
–
–
–
–
–
–
Wander-for-goal
Move-to-goal
Avoid
Avoid-other-robots
Grab-trash
Drop-trash
• Affordances
– Orange=goal
– Green=robot
– Blue=trashcan
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Dimensional score:
Homogeneous
Distributed control
Active cooperation (though minimal)
Individual goal
Chapter 8: Multi-agents
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Example of Heterogeneous Team
• USF USAR team
• Robot had different hardware,
software
• Currently teleoperated
navigation with autonomous
reactive victim detection
• Single goal, active
cooperation
– Confirm a victim with
distributed sensors
– Open door, “spotting” for
navigation in confined
spaces
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Dimensional score:
Heterogeneous
Distributed control (could be central.)
Active cooperation
Single goal
Chapter 8: Multi-agents
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Social Entropy
• Way to measure heterogeneity of a collective
• (go to board-> 4 identical, 4 marsupial)
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Example of Heterogeneous Team
• USC UAV/UGV team
• autonomous helicopter
transporting small robot
• Currently teleoperated
• Single goal, active
cooperation
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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4 Categories of Size
• Size of the collective
– Alone
– Pair
– Limited
• n<<than size of task or environment
– Infinite
• n>>than size of task or environment)
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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3 Categories of Reconfigurability
• Collective reconfigurability
– Static
• The organization doesn’t change, no matter what
– Communicated
• Coordinated rearrangement - Ex. Ordered to change
formation
– Dynamically
• Changes arbitrarily (esp. due to failure)
• Ex. A robot fails
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Box Pushing: Dynamic
Reconfigurability
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Ex. Dynamic Reconfigurability
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Ex. Dynamic Reconfigurability
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
20
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Physically Reconfigurable Robots
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Categories of Communication
• One robot causes an external change in world that can
be observed by another robot)
• Can minimize interference
Communication Range
- None: robots cannot communicate with other robots
directly
- Near: robots can only communicate with other robots
that are sufficiently near (due to the decaying power of
communication signal with distance),
- Infinite: robots can communicate with any other robot.
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Communication Bandwidth
– Infinite
• comms are free
– Motion
• costs as much to communicate as it would to
move
– ex. Box pushing (if other robot can feel the
box, it’s comms)
– Low
• comms costs more than moving from one
location to another
– Zero
• no communication between agents
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Communication Topology
•
•
•
•
Broadcast
Address
Tree
Graph
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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What Do Robots Say to Each Other?
• How do they “talk”?
– Implicit: signaling, postures, smell
– Explicit: language
• Who does the talking?
– “the boss” - Centralized control
– Everybody - Distributed control
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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What do Robots Say?
(after Jung and Zelinsky 02)
• Communication without meaning preservation
– Emitter can’t interpret its own signal
– Receiver reacts in a specific way (stimulus-response)
– Ex. Mating displays, bacteria emit chemicals
• Communication with meaning preservation
– Shared common representation
– Ex. Ant leaves pheromone trail to food, itself & peers can
follow
– Ex. Wolves leave scent markings
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Class Exercise
• Consider the case of resupply, where many multiple
vehicles are in the field and a lesser number of smaller
vehicles exist to carry fuel to them, return to base, and
then carry more fuel out on demand. A field vehicle
emits a message that it needs to be refueled. The
message intensity increases inversely proportional to
the amount of remaining fuel.
• Describe the MAS task.
• Describe the MAS collective.
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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In the end…most popular
• Homogeneous Non-communicating agents
• Heterogeneous Non-communicating agents
• Homogeneous communicating agents
• Heterogeneous communicating agents
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
28
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Class Exercise
• Design a multi-agent team for USAR in terms of
–
–
–
–
Heterogeneity
Control
Cooperation
Goals
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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How to Get
“Right” Emergent Behavior
• Societal Rules vs. behaviors
– Nerd Herd, Maja Mataric
• What if homogeneous, individual goals operating in the same
area?: example-- traffic and traffic jams
• Motivation
– ALLIANCE, Lynn Parker
• What if have single goal, divided among homogeneous agents
and one robot breaks?: example—cleaning up a nuclear spill
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Mataric’s Nerd Herd
and Social Rules
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Explicit Social Rules vs. Behaviors
• Societal Rules
– Ignorant Coexistence
• Basic reactive approach, except robots couldn’t recognize other
robots
• High degree of task interference
– Informed Coexistence
• Recognize each other PLUS simple social rule: if detect robot,
stop and wait for time P; if still there, turn left then resume
move to goal
• Better
– Intelligent Coexistence
• Recognize each other PLUS behavior: repulsed by other robots
concurrent with attraction to move in same direction as the
majority
• Best
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Motivation: ALLIANCE
• Divide and conquer works until a robot fails then what about the failed robot’s area?
• Robot A fails:
– It may realize that it is not doing a good job: becomes
increasingly FRUSTRATED and change behavior (give up)
- it is called ACQUIESCENCE
• Allows other robots to help without task interference
• Robot B is finished with its task
– Sees that it is waiting for Robot A and becomes increasingly
FRUSTRATED until it decides to help - IMPATIENCE
– Goes and helps
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Emotional Waiters
• USF heterogeneous team
– Robot Server, serve food,
count treat removal
– Robot Refiller
– Problem in 1999: refiller
blocked, Server stuck
• Each robot has an emotional
state generator
– Emotions result from
observed progress on task
(and personality, motivation)
• Waiter calls for refill, if
refiller takes long time, gets
impatient, begins to move
towards the refiller
(intercept), eventually goes to
refill station
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
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Emotions: Waiters
Waiter
Serve
Refiller
Request
Wait
Hurry
Impatient
Go
Serve
Intercept
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Refill
Go
Home
Chapter 8: Multi-agents
Get
Intercept
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Example: Comms using ACL
Waiter
Serve
Refille
r
Request
Impatient
Intercept
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Wait
(achieve
:sender butler
:receiver leguin
:reply-with 1234
:language plain
:ontology waiters
:content refill
)
Chapter 8: Multi-agents
Refill
Hurry
Get
Intercept
36
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Cont.
Waiter
Serve
Refiller
Request
Impatient
Intercept
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Wait
(achieve
:sender butler
:receiver leguin
:reply-with 1234
:language plain
:ontology waiters
:content hurry
)
Chapter 8: Multi-agents
Refill
Hurry
Get
Intercept
37
8
Cont.
Waiter
Serve
Refiller
Request
Impatient
(achieve
:sender butler Wait
:receiver leguin
:reply-with 1234
:language plain
:ontology waiters
:content meet me half way
)
Hurry
Get
Intercept
Intercept
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Refill
Chapter 8: Multi-agents
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Summary
• Many, cheap robots are often better than single,
expensive robot
• Multi-agents are generally at least reactive, sometimes
hybrid deliberative/reactive
• Dimensions for categorizing:
– Heterogeneity, control, cooperation, and goals
– (may change dynamically)
• Interference is a big problem
– Social rules
– Emotions, Motivation
• Social entropy can be used to measure heterogeneity
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
39
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Review Questions
• What are the dimensions of a multi-agent system?
– Heterogeneity, control regime, cooperation, goals
• What are the four axes of a task in a collective?
– time, subject of action, movement, dependency
• What are the four axes of a collective?
– composition, size, communications, reconfigurability
• Which is more likely to fail to in the field?
– a team R with 1 member of caste 1 and 5 members of caste 2
– A team R with 6 members of caste 1
Introduction to AI Robotics (MIT Press),
copyright Robin Murphy 2000
Chapter 8: Multi-agents
40