Multi-Agent Systems
A (very)brief introduction
@itsmeritesh
Natural vs. Artificial
Engineering
Natural Artificial
-Made of autonomous agents capable
of playing several roles.
- Autonomous actions by agents...
What’s the Engineering Solution?
A hybrid model which
mimics natural engineering.
A related video is available on http://riteshnayak.com/xconf
The goal of multiagent systems’ research
is to find methods that allow us to build
complex systems composed of
autonomous ...
What’s different
• Completely autonomous agents that act out
of self interest.
• No constraints on inputs (Open World
Prog...
Lets See an example!!
Why is this important
• To simulate events with real life actors.
• To learn about evolutionary characteristics of
a model...
Desirable Characteristics of Agents
• High predictability in behavior
• Operability in uncertain conditions.
• Resilient t...
Emergence
• Designing Objective
functions and payoffs in a
way so that local decisions
of agents collectively result
in op...
Remember Game of Life ??
Evolution
Prebiotic Soup Unicellular Organisms
Multicellular Organisms
A related video is available on http://riteshnayak....
Technologies
• NetLogo: http://ccl.northwestern.edu/netlogo/
• VisualBots. http://www.visualbots.com/index.htm
• MASON.
ht...
NetLogo
Features
• NetLogo is a cross-platform multi-agent
programmable modeling environment.
• Built and maintained out of Northw...
Mars Rover #WIN
Termite mound
• A termite mound is work of art
• The temperature inside the mound has to
remain a constant 31 deg.
• Termi...
Modelling
• Autonomous actions by agents based on self-
interest functions like beliefs, desires,
intentions, etc (Rationa...
Prisoner’s Dilemma
Player A
PlayerB
C
D
C D
5 , 5 0 , 10
10 , 0 1 , 1
A related video is available on http://riteshnayak.c...
Stag Hunt
Hunter A
HunterB
Stag
Hare
Stag Hare
:D 30, :D 30 x-( 0 , 10
10 , x-( 0  1 , 1
Equilibrium Concepts
The simplest form of Nash equilibrium
is one where each player makes a
rational choice with no belief...
MAS Borrows from
• Rational Choice theory
• Game theory
• Stochastic Networks
• Auction theory, negotiations and mechanism...
Mechanism Design
• Refers to the design principles behind an
auction or a voting process that can be used
to favor specifi...
Interesting Applications
Weather Forecasting
There is a lot of work being done
to model climate and
implications of climate change
etc. A domain th...
Self Optimizing Networks
Optimal Wifi using robot routers
Realism in Games
A related video is available on http://riteshnayak.com/xconf
The Grand DARPA Challenge
Requires teams to build an autonomous vehicle capable of
driving in traffic, performing complex ...
Disaster Recovery
• Work done by my classmates at CSTEP.in
• Using technology to shape public policy
• Use SimCity as a ba...
My Project
• Multi-Agent based simulation of a
Normative/Incentive system for Content
Aggregation on Online Forums
• Main ...
Some results from this project
LoyalUser
• Posts
Regularly
• Forgiving
• Satisfied
with
answers
• Closes q’s
early
• 1 category
RegularUser
• Less
freque...
Last but one slide
• MAS research is a relatively new field for
computer scientists.
• Lot of applications in many differe...
References
• Fundamentals of Multiagent Systems - Jos´e M Vidal -
http://jmvidal.cse.sc.edu/papers/mas-20070824.pdf
• Cour...
MAS
MAS
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MAS

  1. 1. Multi-Agent Systems A (very)brief introduction @itsmeritesh
  2. 2. Natural vs. Artificial
  3. 3. Engineering Natural Artificial -Made of autonomous agents capable of playing several roles. - Autonomous actions by agents based on self interest. - Structure is a result of evolution and local adjustments. - Made of parts custom built for a specific purpose - Well defined functionality for each part. - Structure is designed into its present shape. Living beings behave more like societies than machines according to the definitions. Courtesy: Course Slide
  4. 4. What’s the Engineering Solution?
  5. 5. A hybrid model which mimics natural engineering. A related video is available on http://riteshnayak.com/xconf
  6. 6. The goal of multiagent systems’ research is to find methods that allow us to build complex systems composed of autonomous agents who, while operating on local knowledge and possessing only limited abilities, are nonetheless capable of enacting the desired global behaviors.
  7. 7. What’s different • Completely autonomous agents that act out of self interest. • No constraints on inputs (Open World Programming) • Limited knowledge (don’t think bluegene) • Interaction between autonomous agents determined based on self interest function.
  8. 8. Lets See an example!!
  9. 9. Why is this important • To simulate events with real life actors. • To learn about evolutionary characteristics of a model. • Model societies, colonies, groups etc and learn about herd behavior (ex: How do perfectly rational humans create traffic deadlocks?) Humans are individually smart and collectively stupid.
  10. 10. Desirable Characteristics of Agents • High predictability in behavior • Operability in uncertain conditions. • Resilient to failures. • Optimal performance for given situations • Mathematical tractability to the finest detail.
  11. 11. Emergence • Designing Objective functions and payoffs in a way so that local decisions of agents collectively result in optimizing a global objective function. • You cannot code for emergence. • Emergent behaviors are not always desirable. 
  12. 12. Remember Game of Life ??
  13. 13. Evolution Prebiotic Soup Unicellular Organisms Multicellular Organisms A related video is available on http://riteshnayak.com/xconf
  14. 14. Technologies • NetLogo: http://ccl.northwestern.edu/netlogo/ • VisualBots. http://www.visualbots.com/index.htm • MASON. http://www.cs.gmu.edu/~eclab/projects/mason/ • Repast. http://repast.sourceforge.net/ • Java Agent Development Framework http://jade.tilab.com/
  15. 15. NetLogo
  16. 16. Features • NetLogo is a cross-platform multi-agent programmable modeling environment. • Built and maintained out of Northwestern University. • Uses a variant of LOGO Lets see a demonstration
  17. 17. Mars Rover #WIN
  18. 18. Termite mound • A termite mound is work of art • The temperature inside the mound has to remain a constant 31 deg. • Termites are autonomous beings. They are hard wired to do only one thing!! A related video is available on http://riteshnayak.com/xconf
  19. 19. Modelling • Autonomous actions by agents based on self- interest functions like beliefs, desires, intentions, etc (Rational Choice – or utility maximization – John Stuart Mills) • Interaction between Agents can be modeled as a game, auction (common resources), vote (master-slave setup) etc.
  20. 20. Prisoner’s Dilemma Player A PlayerB C D C D 5 , 5 0 , 10 10 , 0 1 , 1 A related video is available on http://riteshnayak.com/xconf
  21. 21. Stag Hunt Hunter A HunterB Stag Hare Stag Hare :D 30, :D 30 x-( 0 , 10 10 , x-( 0  1 , 1
  22. 22. Equilibrium Concepts The simplest form of Nash equilibrium is one where each player makes a rational choice with no belief (or a least biased belief) about the other players.
  23. 23. MAS Borrows from • Rational Choice theory • Game theory • Stochastic Networks • Auction theory, negotiations and mechanism design. • Chaos theory, complex systems and theory of emergence.
  24. 24. Mechanism Design • Refers to the design principles behind an auction or a voting process that can be used to favor specific outcome • In an auction, the seller’s choice is to sell at the highest possible price. How do you get the agents to quote higher prices.
  25. 25. Interesting Applications
  26. 26. Weather Forecasting There is a lot of work being done to model climate and implications of climate change etc. A domain that has seen a lot of action in last decade.
  27. 27. Self Optimizing Networks
  28. 28. Optimal Wifi using robot routers
  29. 29. Realism in Games A related video is available on http://riteshnayak.com/xconf
  30. 30. The Grand DARPA Challenge Requires teams to build an autonomous vehicle capable of driving in traffic, performing complex maneuvers such as merging, passing, parking and negotiating intersections. Prize money is $2 million, $1million and $500k respectively A related video is available on http://riteshnayak.com/xconf
  31. 31. Disaster Recovery • Work done by my classmates at CSTEP.in • Using technology to shape public policy • Use SimCity as a base framework for modelling agents. A small video of the simulation
  32. 32. My Project • Multi-Agent based simulation of a Normative/Incentive system for Content Aggregation on Online Forums • Main objectives – To build a system of norms and incentives for knowledge aggregation on an online forum – Mechanism design to increase activity on the forum and also keep the network from saturating
  33. 33. Some results from this project
  34. 34. LoyalUser • Posts Regularly • Forgiving • Satisfied with answers • Closes q’s early • 1 category RegularUser • Less frequently than loyal • Less forgiving • Waits for more answers • At least 2 categories BounceUser • Participates rarely • Reply sometimes • Mostly simulate redirects from search engines • Don’t close questions.
  35. 35. Last but one slide • MAS research is a relatively new field for computer scientists. • Lot of applications in many different fields. Will gain a lot of prominence very soon. • Skeptics doubt results due to inconsistency. • Hope you figured the playing God part.
  36. 36. References • Fundamentals of Multiagent Systems - Jos´e M Vidal - http://jmvidal.cse.sc.edu/papers/mas-20070824.pdf • Course on MAS at my institute IIIT – Bangalore (course page http://osl.iiitb.ac.in/wiki/index.php/Multi-Agent_Systems) • Prof Srinath Srinivasa for all anecdotes/ examples etc. • Evolution of Co-operation – Robert Axelrod • C.H. Papadimitriou. Algorithms, Games, and the Internet. Proc. STOC-2001, ACM Press, 2001. Invited talk write- up.(URL:http://www.eecs.harvard.edu/~parkes/cs286r/spring02/papers/stoc01.pdf) • Thanks to DARPA, Google Image search, wisegeek.com and Wikipedia for the images.

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