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AutoPilot Year 1 Results Principal Investigators: Jerry Stach E.K. Park University of Missouri - Kansas City.

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Presentation on theme: "AutoPilot Year 1 Results Principal Investigators: Jerry Stach E.K. Park University of Missouri - Kansas City."— Presentation transcript:

1 AutoPilot Year 1 Results Principal Investigators: Jerry Stach E.K. Park University of Missouri - Kansas City

2 Questions Posed By Sponsor 1. Decentralized Scaleable Trader (a) How do you maintain global information about a set of available services without a central point of failure? (b) What are the Query and Update costs of a decentralized Trader? University of Missouri - Kansas City

3 Questions Posed By Sponsor 2. Agent Health Monitor Investigate ways to monitor large numbers of mobile/distributed agents with minimal effect on overall systems performance. University of Missouri - Kansas City

4 Questions Posed By Sponsor 3. Mobile Agent Patterns As work on the first two categories progresses, document any design patterns that emerge. University of Missouri - Kansas City

5 Engineering Problems - Current System Only about 10 3 agents can run concurrently in the current network. The answers to the Sponsors questions must scale at least one order of magnitude: 10 4 concurrent mobile agents 10 4 service nodes with 10 – 20 service instances per node the number of Trader Places approaching 10 3 2*10 3 entries per directory. University of Missouri - Kansas City

6 Underlying Causes The current limitation of 10 3 Agents implies Band Limiting Band Limiting can Occur in the Service Place CPU if mean processing time is high relative to agent arrivals Band Limiting can occur in the Network as a function of message intensity – focused overloads (agent Trader Place) – agent collaboration or management University of Missouri - Kansas City

7 Band Limiting in the Service Place CPU Possible Strategies –Accelerate CPUs –Increase number of CPUs Acceleration may not place the power in the right locations Increasing the number of Service Places increases band width demand of the network University of Missouri - Kansas City

8 Implications If arbitrary increases in the number of Service Places are to be avoided, concurrency is implied to maximize CPU utilization –agents should have capability to function as autonomous distributed processes –mobility must include agent reasoning about local congestion and distance University of Missouri - Kansas City

9 Band Limiting in the Network Strategy –Minimize number of messages in the Agent Colony messages associated with accessing the Trader Place regarding Service offerings [Sponsor Question 1] messages associated with managing the colony of agents [Sponsor Question 2] University of Missouri - Kansas City

10 Implication Minimizing the number of messages to the Trader Places implies some intermediate process in the Architecture that can parse the Trader Place vector for multiple agents at a Service Place. The agent must then be able to interpret the vector relative to its own preferences. The mobility decision is implied at the agent (lowest Architecture level) not at the Trader (highest Architecture level) University of Missouri - Kansas City

11 Implication Minimizing the number of messages associated with population management implies being able to anticipate the location of a given agent to eliminate exhaustive search or suspension of the population. This implies higher levels of the Architecture must understand the mobility decision in order to locate agents in the network University of Missouri - Kansas City

12 Problem Synthesis A multi - level Architecture is implied Agent Service Planner Trader University of Missouri - Kansas City

13 Problem Synthesis Migration is fundamental to the answers to Questions 1, 2 –agents are situated and must move to a subsequent Service Place based upon service attributes of time, cost, quality (perception) a context of total moves that satisfies their service sequences (local optimization) University of Missouri - Kansas City

14 Problem Synthesis Agent migrations should not adversely effect the network system –moves should be sensitive to network dynamics such as local congestion and path length (global optimization) –in the large, individual agent migration decisions should cause load leveling at Service Places and traffic distribution without a central authority (emergent behavior) University of Missouri - Kansas City

15 Proposed AutoPilot Architecture Agent Service Planner Trader Topologist Service Place Trader Place AutoPilot Network Router University of Missouri - Kansas City

16 Research Implications: Distributed Artificial Intelligence - there is an Artificial Intelligence Sub Problem - there is a Distributed Processing sub problem - there is a Network sub problem University of Missouri - Kansas City

17 Artificial Intelligence Sub Problem Given a set of agent preferences for time to service, cost of service and quality of service, select the most desirable location from a set of possible locations that conform to the agents preferences This is a multi-attribute programming problem University of Missouri - Kansas City

18 Distributed Processing Sub Problem Given a set of Service Places and the service set of each Service Place, find an optimal assignment of Services to the Service Places subject to the Service Place environments This is a multi-processor task assignment problem University of Missouri - Kansas City

19 Network Sub Problem Given a sequence of Services specified by the agents work flow signature and a set of feasible Service Places, construct a optimal itinerary that minimizes total trip time This is a graph theory problem (trip planning) University of Missouri - Kansas City

20 Strategy Solve academic problems in a manner that produces engineering solutions as well as new knowledge Select solution techniques that integrate the three classes of sub problems University of Missouri - Kansas City

21 Research Approach: Composition not Decomposition 1. Obtain a solution for the assignment of Services to Service Places 2. Obtain a solution to for agent's attribute based perception of Service Places 3. Integrate the results from (1) and (2) forming a mobility heuristic 4. Validate the heuristics by simulating situated multi-agents in a network of Service Places. 5. Formulate Trader Place Inquiry/Update Costs University of Missouri - Kansas City

22 Overview of Assignment of Services to Service Places Each agent carries a work flow signature for the possible processing sequences of its task graph A B C D E Work Flow Signature = A;B;(C+D);E University of Missouri - Kansas City

23 Assignment of Services continued Build an interior graph of the signature. Weight interior edges with the payload size from task I to task J A B C D E 1.0 2.8 3.6.8 1.1 Input is initial agent payload and a scaling matrix University of Missouri - Kansas City

24 Assignment of Services continued Connect each interior Service node to every Service Place supporting that service subject to the agents preference criteria Weight the edges from the Services to the Service Places by agent preference for the Service Place University of Missouri - Kansas City

25 Assignment of Services continued University of Missouri - Kansas City

26 Assignment of Services continued Weighting of edges from Services to Service Places University of Missouri - Kansas City

27 Assignment of Services continued A B D C E C a,b C b,d C b,c C d,e C c,e SP1 SP2 SP3 W a,sp1 W a,sp3 W b,sp1 W d,sp2 W e,sp3 W c,sp3 University of Missouri - Kansas City

28 Assignment of Services continued A B D C E C a,b C b,d C b,c C d,e C c,e SP1 SP2 SP3 W a,sp1 W a,sp3 W b,sp1 W d,sp2 W e,sp3 W c,sp3 Not SP1 Find a minimum cut to the network - Services A,B,C are assigned to SP1 University of Missouri - Kansas City

29 D E C d,e SP2 SP3 W d,sp2 W e,sp3 Re-compute weights, find a new minimum cut, D is assigned to SP2, E is assigned to SP3 Assignment of Services continued Final Service Assignments SP1:= A,B,C SP2 := D SP3 := E University of Missouri - Kansas City

30 Improving Performance We do not want to consider 10K Service Places for each agent –Observations several locations may be equivalent by agent perception of time to service, cost of service and quality of service if we could pick the Service Places to consider in the right order, we should assign all services in a relatively few iterations University of Missouri - Kansas City

31 Improving Performance continued Leads to the multi attribute programming problem An agent perceives each Service Place by its attributes (time, cost,quality) If the agent could rank the Service Places by these attributes, we could generate equivalence classes of Service Places University of Missouri - Kansas City

32 Improving Performance continued Sp3 SP5 SP4 SP2 SP1 SP5 SP3 SP2 SP1 SP4 SP3 SP2 SP1 SP4 SP5 Equivalence By TimeEquivalence By CostEquivalence By Quality SP3 is an non-dominated Service Place in intersection of the first equivalence class for each attribute. Have the graph algorithm consider SP3 first. University of Missouri - Kansas City

33 Multi-Attribute Programming Problem We cannot use a linear weighting scheme to rank nodes because time, cost and quality do not normalize an agents constant perception of its environment is time the Topologist can provide the Service Planner the current geodasic to a Service Place (router interface) University of Missouri - Kansas City

34 Multi-Attribute Programming continued Humans distort time by attributes –long car ride for a bargain is viewed as acceptable to some limit of time –a one hour poor presentation is long –a two hour great movie is short Why not let the agent distort time by the attributes of Service Places? –Need an objective function University of Missouri - Kansas City

35 Functions of Cost and Quality on Time University of Missouri - Kansas City

36 Quantifying agent perception In AutoPilot we limit max_distortion to twice the diameter of the network so an agent perceives the time to initiate service from nearly zero to twice the network diameter depending on its perception of the Service Place. University of Missouri - Kansas City

37 Demonstrations of Research Results Description of Base Cases presented Results viewed by visual front end single agent simulations –link speeds are negligible heuristic search for service - equal preferences for time, cost, quality migration by preference for time migration by preference for cost University of Missouri - Kansas City

38 Demonstrations of Research Results continued Multi-agent simulation –colony of 100 agents –all services offered on all nodes –arrival rates to network are high relative to processing time –transmission times are negligible –hope to see second order network effects as emergent behavior University of Missouri - Kansas City

39 London New York Sydney Los Angeles 1 2 3

40 Network Second Order Effects as a result of multi-agent interaction Emergent Colony Behavior Under network loading individual agent decisions aggregate to Service Place load-leveling in the absence of any central network or Trader authority. Expected BehaviorDesired Behavior Legend CPU Utilization Service Place Queue Length Service Place Agent Age

41 Accomplishments 1. Obtain a solution for the assignment of Services to Service Places Complete 2. Obtain a solution to for agent's attribute based perception of Service Places Complete 3. Integrate the results from (1) and (2) forming a mobility heuristic Complete 4. Validate the heuristics by simulating situated multi-agents in a network of Service Places. –Partially Complete, base cases only, not fully debugged 5. Formulate Trader Place Inquiry/Update Costs –Equations presented in year end report

42 Proposed Research Activities Year 2 Focus on remaining Sponsor questions: – 1(a). Decentralized Scaleable Trader How do you maintain global information about a set of available services without a central point of failure? –2. Agent Health Monitor Investigate ways to monitor large numbers of mobile/distributed agents with minimal effect on overall systems performance subject to the Trader cost formula from Year 1 results. University of Missouri - Kansas City

43 Proposed Research Activities Year 2 continued generalize the multi-attribute function for n attributes fully debug the simulator and extend to accommodate a definition of the Sponsors network (links/ number nodes) extend the simulator to include Trader Place update policies (interval, random..) University of Missouri - Kansas City

44 Proposed Research Activities Year 2 continued study the relationship between emergent behavior and the Trader Place update policy improve visualization post processor in first half year produce two journal papers on agent mobility –multi attribute programming solution –general formulation of agent mobility University of Missouri - Kansas City

45 Proposed Research Activities Year 2 continued study the applicability of Artificial Life principles to agent mobility in large colonies. University of Missouri - Kansas City

46 Current Status Summary of progress against proposal –On-track in pursuing Sponsor questions with respect to research activities –Behind in debugging the simulator - not ready for delivery yet University of Missouri - Kansas City


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