Distributed Intelligence: Multi-Agent Programming

1. Distributed Intelligence:Multi-Agent Programming CS-350 Research Paper Presentation Jon Saliers

2. Introduction • What is Distributed Intelligence? • What is Multi-Agent Programming? • Do many unintelligent agents make an intelligent union?

3. 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

4. ‘Unintelligent’ Agents • Each agent is specialized, not necessarily unintelligent. • Only performs its own function. • Limited amount of memory.

5. ???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

6. 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.

7. 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.

8. 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

9. 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.

10. Northeast Power Grid Failure

11. 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.

12. 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

13. 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.

14. Questions?