planning and coordination in a multi-agent environment
DESCRIPTION
Planning and Coordination in A Multi-Agent Environment. Gökay Burak AKKUŞ 2003700717 cmpe530. Agent. An agent is something that acts. An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators. Planning. - PowerPoint PPT PresentationTRANSCRIPT
Boğaziçi University
Planning and Coordination in A Multi-Agent Environment.
Gökay Burak AKKUŞ
2003700717
cmpe530
Gökay Burak AKKUŞ
Agent
An agent is something that acts.
An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators.
Gökay Burak AKKUŞ
Planning
The task of coming up with a sequence of actions that will achieve a goal is called planning
Gökay Burak AKKUŞ
Planning
Classical PlanningCurrent State →→ Desired GoalFully ObservableDeterministicFiniteStaticDiscrete
Non-Classical PlanningHierarchical, Decision-Theoretic, Continual, Distributed
Gökay Burak AKKUŞ
An agent plans on the basis of an incrementally learnt world model and reacts on the basis of incrementally learnt values that indicate the usefulness of his potential actions.
Gökay Burak AKKUŞ
Planning
Single-Agent EnvironmentsThe agent is alone
Multi-Agent EnvironmentsOther agents in enviroment considered
The solution to a global problem emerges from the collective activities of independent agents.
Gökay Burak AKKUŞ
Planner
Figure 1 : Planner [7]
Gökay Burak AKKUŞ
Multi-Agent Planning
CooperationJoint-goals & plans
CoordinationMulty-body planning(centralized planning agent)
Synchronization
Cooperation - Competition
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Planning Agent
A Single Agent for Planning & Coordination
Execution & monitoring
Re-Planning(when something goes wrong) in real-time responses
Adaptation to dynamic environment
Performance Prediction of agents
A single agent search for multi-agent problems.Search for actions to be taken
Search in state space (Agent + Action)
Gökay Burak AKKUŞ
Planning Agent
Distributed PlanningCooperative Distributed Planning (CDP), takes the individual planning process and distributes it among a subset of an agent society such that the generation and execution of a plan requires the interaction of several specialized agents
Negotiated Distributed Planning (NDP), is based on the concept that agents should primarily be focused on the individual, but can use plans as a means of coordinating actions
Gökay Burak AKKUŞ
agents should work together according to the following model:1.Each agent works on large grained sub-problems2.Agents should be able to generate partial results, even if these
results are uncertain or the agent is missing information3.Agents should communicate partial results to other agents
asynchronously as the partial results are developed4.Agents should use partial results from other agents to help
resolve their own uncertainties and guide individual solutions
Our planning agent helps in these, as it is the root of coordination hierarchy
Gökay Burak AKKUŞ
Learning, Planning, Reacting
Figure-2 :relationships between learning, planning, and reacting.
Gökay Burak AKKUŞ
Some Definitions
Reactive Coordination vs. Planning coordinationThe Knowledge needed:
Ag = {A1, ...An} : Available Agents in EnvironmentSet of Actions that can be performed by an agent in an environmentSet of Actions that can be performed at a certain stateSet of agents that can carry out actions to reach a successor state (S → T)Estimated usefullnes of actionsValidity, Satisfiability of Results, Partial results
Joint Learning: Learning is realized by the agents through adjusting the estimates of their actions’ usefulness.
Gökay Burak AKKUŞ
Performance Measures
A performance measure embodies the criterion for success of an agent’s behavior.
Objective performance measure : Typically one imposed by the designer.
As a general rule it is better to design performance measures according to what one actually wants in the environment, rather than according to how one thinks the agent should behave.
Gökay Burak AKKUŞ
Performance Evaluation
PACE : Performance Analysis and Characterisation EnvironmentPACE provides a means of dynamically obtaining runtime estimates for different applications on different resources through the performance information services framework.multiple (and often conflicting) metrics must be considered
Gökay Burak AKKUŞ
Metrics
Total execution time
Average advance time
Resource Utilization Rate
Load balancing level
Gökay Burak AKKUŞ
What To Do?
A certain goal is defined,Planning agent searches the problem domain for possible instances of agents working in that domain (agent society)
If problem involves more domains, tries to divide problem into sub-problems considering domain interactions
Planning agent reaches the execution history of agents it will deal with.Planning agent evaluates the agent in [0..1] scale by means of
Goal Satisfaction, (d1)Resource usage, (d2)Problem usefulnes, (d3)Coordination capabilities (d4)...0<= d1*w1+d2*w2+d3*w3+d4*w4+...+dn*wn <= 1w: specifies the impotance weight of a metric for the problem
Then, it generates a joint plan using the ranking of agents to employ appropriate agents on specific tasks,Monitors the ongoing activities, communication between agents, and when needed Re-planning takes place
Gökay Burak AKKUŞ
Evaluation
For a better planning prediction of next action of an agent, in terms of predefined metrics, is important.The prediction of next action has two components:
Previous experiences about the agent,Possible results that will be generated by the agent for the new problem
So, a model that can be used to predict future behavior of an agent must be generated.Possible modelling options:
Extrapolation,
Gökay Burak AKKUŞ
Main Goal
A model that can work both under perfect and imperfect monitoring needs to be developed for evaluation process of agents.underlying knowledge structure, previous task experiences and solution generation capabilities over a feasible time period, will be used as weights of evaluationcoordination for timely samplings of goal satisfaction for multi-agent systems will be taken into account
Gökay Burak AKKUŞ
References
[1] William Hansel Turkett, Jr. ([email protected]), Robust Multiagent Plan Generation and Execution with Decision-Theoretic Planners Dissertation Proposal, Department of Computer Science and Engineering University of South Carolina Columbia, SC 29208, Spring 2003[2] Gerhard Weiß ([email protected] ), An Architectural Framework for Integrated Multiagent Planning, Reacting, and Learning Institut für Informatik, Technische Universitat München D-80290 München, Germany[3] Romen I. Brafman ([email protected]), Moshe Tennenholtz ([email protected]), Learning to Coordinate Efficiently: A Model Based Approach, 2003[4] Michael Brenner ([email protected]), MAPL: a Framework for Multiagent Planning with Partially Ordered Temporal Plans, Institut für Informatik, Universitat Freiburg, 79110 Freiburg, Germany[5] Junwei Cao, Subhash Saini, Stephen A. Jarvis, Daniel P. Spooner, Helene N. Lim Choi Keung, Graham R. Nudd High Performance Systems Group, University of Warwick, Coventry, UK, Performance Prediction and its use in Parallel and Distributed Computing Systems[6] Nils J. Nilsson, Artificial Intelligence A New Sysnthesis, Stanford University, 1998[7] Jonathan Gratch, Reasoning about Multiple Plans in Dynamic Multi-agent Environments, Information Sciences Institute University of Southern California, October 1998.
Gökay Burak AKKUŞ
Thanks...Questions ?