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Distributed Intelligence: Multi-Agent Programming. CS-350 Research Paper Presentation Jon Saliers. Introduction. What is Distributed Intelligence? What is Multi-Agent Programming? Do many unintelligent agents make an intelligent union?. Distributed Intelligence. Concept of team control

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distributed intelligence multi agent programming

Distributed Intelligence:Multi-Agent Programming

CS-350 Research Paper Presentation

Jon Saliers

introduction
Introduction
  • What is Distributed Intelligence?
  • What is Multi-Agent Programming?
  • Do many unintelligent agents make an intelligent union?
distributed intelligence
Distributed Intelligence
  • Concept of team control
  • Specialization of functions or behaviors
  • Inter-system dependencies minimized
  • Used in component-based automation
  • Solution of complex problems
    • Increase speed and efficiency of problem completion
    • ‘Learn’ from past experiences
unintelligent agents
‘Unintelligent’ Agents
  • Each agent is specialized, not necessarily unintelligent.
  • Only performs its own function.
  • Limited amount of memory.
intelligent union
???Intelligent Union???
  • The whole is greater than the sum of the parts!
  • Specialization of function (“I do mine, you do yours”)
  • Work toward a common goal
multi agent programming map
Multi-Agent Programming (MAP)
  • Agents are not necessarily physical agents.
  • Programmers use a population of virtual computer agents.
    • The agents work together to solve problems using distributed intelligence.
    • Also known as “swarm-intelligence”.
  • “Swarming” – behavior of certain social insects (ants, bees, etc)
    • Swarm when moving hive to a new site.
    • Programs model this swarming insect behavior.
advantages of map
Advantages of MAP
  • Behavior is emergent.
    • The system learns as it gains experience.
  • Many computer programs explicitly mimic biological systems.
    • These biological systems consist of many entities (agents).
    • The entities work together to achieve a goal.
    • Each entity has its own duties/functions.
disadvantages of map
Disadvantages of MAP
  • Behavior is emergent, not pre-planned.
    • Programmers cannot predict what behavior will occur.
    • Agents lose sight of original goal as they learn – necessity for programmed reinforcers.
  • Failure through success.
    • Each agent performs its own functions properly, but the system as a whole fails.
    • Northeast Power Grid Failure
northeast power grid failure
Northeast Power Grid Failure
  • During power drops and surges, each sub-station (agent) is programmed to shut down for protection.
  • Each sub-system performed its duty properly…
  • And the larger system, the distributed system, failed miserably.
  • Why? The sub-systems do not see the big picture (overall scope), only their own duties.
emergent behavior
Emergent Behavior
  • Unanticipated, learned behavior
  • Unpredictable behavior
    • Emergent behavior is not programmed
    • Behaviors cannot be deduced from low-level programmed behaviors
  • Emergent behavior occurs in a group, but is not programmed into any member of the group.
emergent behavior12
Emergent Behavior
  • Emergent behavior can occur in any population, including a computer population.
  • Emergent behavior is not artificial intelligence
    • Artificial intelligence behaviors and reactions are predictable
conclusions
Conclusions
  • Multi-agent distributed intelligence systems serve many purposes, such as complex problem solving.
  • Some systems are directly modeled after biological systems.
  • Emergent behavior is both an advantage and disadvantage of these systems.