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Multiagent Systems & Societies of Agents (II)

Multiagent Systems & Societies of Agents (II). Authors : Michael N. Huns & Larry M. Stephens Speaker : Shabbir Ali Syed CSCE 976, April 8 th 2002. Agent Interaction Protocols. Govern the exchange of a series of messages among agents Case 1: Agents have conflicting goals

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Multiagent Systems & Societies of Agents (II)

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  1. Multiagent Systems &Societies of Agents (II) Authors: Michael N. Huns & Larry M. Stephens Speaker: Shabbir Ali Syed CSCE 976, April 8th 2002

  2. Agent Interaction Protocols Govern the exchange of a series of messages among agents Case 1: Agents have conflicting goals Case 2: Agents have similar goals

  3. Agents with conflicting goals Conflicting goals or simply self-interested • Maximize payoff (utility functions)

  4. Agents with similar goals Objective: maintain globally coherent performance without violating autonomous behavior of agents • Determine shared goals • Determine common tasks • Avoid unnecessary conflicts • Pool knowledge and evidence

  5. Some Interaction Protocols Coordination Protocols Cooperation Protocols Contract Net Blackboard Systems Negotiation Multi-Agent Belief Maintenance Market Mechanisms

  6. 1. Coordination Protocols Done between multiple agents to satisfy individual or group goals Why coordination is needed: • Maintain dependencies between actions • Meet global constraints • When no one agent has sufficient competence, resources, or information to achieve system goals

  7. Distributed AI (DAI) Distributing data and control Agents have autonomy to generate new actions and to decide which goals to pursue next Disadvantages: • KB is distributed, so each agent has only a partial and imprecise perspective of KB • Degree of uncertainty in actions • Difficult to attain coherent global behavior

  8. Goal Graph It is a AND/OR graph with the leaves representing the goals Activities are: • Defining Goal Graph, including identification and classification of dependencies. • Assigning particular regions of the graph to appropriate agents • Controlling decisions about which areas of the graph to explore • Traversing the graph • Ensuring that successful traversal is reported

  9. Agent Structures Commitment • Pledges to undertake a specified course of action • As situation changes agents must evaluate whether existing commitments are still valid • Internal and Belief consistent Convention • Provide a means to manage commitments in changing circumstances • Provides degree of predictability: Agents can take into consideration future conflicts, dependencies, and activities of other agents

  10. Limited B/W Social Convention INVOKE WHEN Local commitment dropped Local commitment satisfied ACTIONS Rule1: IF Local commitment satisfied THEN inform all related commitments Rule2: IF Local commitments dropped because unattainable or motivation not present THEN inform all strongly related commitments. Rule3: IF Local commitments dropped because unattainable or motivation not present AND communication resources not overburdened THEN inform all weakly related commitments.

  11. Basic Joint Action Convention • INVOKE WHEN Status of commitment to joint action changes Status of commitment to attaining joint action in present tem context changes Status of joint commitment of a team member changes. ACTIONS Rule1: IF status of commitment to joint action changes OR IF status of commitment to present team context changes THEN inform all other team members of these changes Rule 2: IF status of joint commitment of a team member changes THEN determine whether joint commitment still viable.

  12. Cooperating Agents Each agent should share status of its commitment to: • the shared objective • the given team framework If belief changes, should inform all agents

  13. 2. Cooperation Protocols Divide and Conquer Approach • Smaller sub-tasks require less capable agents • Fewer resources Distributing Criteria: • Avoid overloading critical resources • Assign tasks to agents with matching capabilities • Make an agent with wide view assign tasks to other agents • Assign overlapping responsibilities to agents to achieve coherence • Assign highly independent tasks to agents in spatial or semantic proximity-minimizes communication and synchronization costs • Reassign tasks if necessary for completing urgent tasks

  14. Methods for task distribution

  15. 3. Contract Net Best know and widely applied to distribute tasks. Connection problem: finding an appropriate agent to work on a given task Manager: • Announces a task that needs to be performed • Receives and evaluates bids from potential contractors. • Award a contract to a suitable contractor. • Receive and synthesize results. Contactor: • Receive task announcement • Evaluate my capability to respond • Respond (decline, bid) • Perform the task if my bid is accepted • Report my results.

  16. Contract Net

  17. Task Announcement • Addressee: Contractor • Eligibility Specification: Contractors should meet certain criteria to make bids. • Task Abstraction: A brief description of the task, is used by contractors to rank tasks from several task announcements. • Bid Specification: Tells contractors , what info. must be provide with the bids.Manager compares different contractors on basis of bids. • Expiration Time: Deadline for receiving bids.

  18. Limitations • Task must be awarded anyway, even if a better contractor is busy. • Manager is under no obligation to inform other customers that an award has already been made. • All potential contractors can be busy and so not send bids to the manager • A potential contractor ranks the proposed task below other tasks, and so may not send bids. • No contractor even if idle is able tohandle the task.

  19. Proposed solution • Manager: Requests immediate response bids. Contractors: eligible but busy. ineligible uninterested. • Manager: directed contracts Contractors:acceptance refusal

  20. 4. Blackboard Systems Characteristics of BB systems • Independence of expertise • Diversity of problem-solving techniques • Flexible representation of blackboard information • Common interaction language • Event based activation • Need for control • Incremental solution generation Knowledge source: KS

  21. BB Systems: characteristics Independence of expertise: A specialist (KS) can act independently of the other Diversity of problem-solving techniques: Internal representation of each KS is hidden from others Flexible representation of blackboard information: No restriction as to what can be placed on the blackboard Common interaction language: KS’s should be able to correctly interpret information posted by other KS’S

  22. BB Systems: characteristics Event based activation: KS’s give their preferences and blackboard triggers them whenever it occurs Need for control: Triggered KS, evaluates quality of its contributioninforms Control Component about the costestimates benefits and decides how to trigger for better problem solving Incremental solution generation: KS contributes as needed (refining, contradicting, initiating)

  23. Diagram for blackboard

  24. 5. Negotiation Joint decision reached by two or more agents, each trying to reach an individual goal Features: • Language used by participating agents • Protocols followed by agents as they negotiate • Decision process used for concession, criteria for agreement and to determine position

  25. Attributes of negotiation • Efficiency: agents should not waste resources in coming to an agreement • Stability: no agent should have an incentive to deviate from agreed upon strategies • Simplicity: the negotiation mechanism should impose low computational and bandwidth demands on the agents • Distribution: no central decision maker • Symmetry: should not be biased against any agent for arbitrary reasons

  26. Systems for Negotiation Two types • Environment centered • Agent centered

  27. Environment Centered Rules by which agents can interact productively and fairly irrespective of their capabilities or intentions • Task-oriented domain • State-oriented domain • Worth-orienteddomain

  28. Agent Centered Best strategy for an agent to follow in a given environment • Task-oriented domain

  29. Task-Oriented Domain • Agents have set of tasks • Resources needed are available • Agents can achieve tasks without help nor interference • Agents can benefit by sharing some tasks Example: Internet downloading

  30. Example: Internet downloading Constraints • Each agent declares documents it wants • Common documents are assigned by the “toss of coin” • Agents pay for the documents they download • Agents are granted access to all documents in common set Mechanism is simple, accurate, systematic, and distributed (no document downloaded twice)

  31. Agent Centered: Approaches • Speech act classifiers together with a possible world semantics used to formalize negotiation protocols and their components • Unified Negotiation Protocol Assumption: agents are economically rational • Set of agents must be small • Must have a common language • Must have a common problem abstraction • Must reach a common solution

  32. Speech Act An agent forms and maintains its commitments to achieve a task individually iff: • It has not pre-committed itself to another agent to adopt and achieve a task • It has a goal to achieve the task individually • It is willing to achieve the task individually

  33. Unified Negotiation Protocol • Deal: joint plan between agents that would satisfy all their goals • Utility: amount agent is willing to pay minus cost of deal (to be maximized) • Negotiation set:set of all deals that have a positive utility for all agents • Conflict: negotiation set is empty • Compromise: agents agree to negotiate • Co-operative: all deals in negotiation set are preferred by both agents over achieving their goals

  34. IN IN Human(x)=>Mortal(x) Human(socrate) fact fact + + Justification node IN Mortal(socrate) Derived fact

  35. IN IN IN OUT + + - + IN

  36. Drank-Fountain-of-youth(socrate) Human(x)=>Mortal(x) Human(socrate) IN IN OUT + - + MORTAL(SOCRATE) IN

  37. 6. Multiagent Belief Maintenance High level interaction among agents Relies on Truth Maintenance Systems (TMS): Data structure (AI) that keeps track of the truth of a fact in a KB given the truth of the facts it is derived from (which constitute its support or justification)

  38. TMS (or Reason Maintenance System, RMS) • Ensure integrity of agents knowledge • Ensure that its stable • Datum that has a valid justification is believed • Datum that lacks a valid justification is disbelieved • Well founded • Permits no set of its beliefs to be mutually dependent • Logically consistent • Stable at the time consistency is determined and has no logical contradiction • No datum is both believed and disbelieved at same time

  39. Justification based TMS (JTMS) Datum: • Set of justification. • Associated status. • INTERNAL:Believed because of a valid local justification. • EXTERNAL:Believed because another agent asserted it. • OUT: Disbelieved. A communicated Datum must be: • INTERNAL to at least one of the agents that believes it. • Either INTERNAL or EXTERNAL to the rest.

  40. TMS before Justification

  41. Resultant Network

  42. Multi-agent TMS Invoked by addition or removal of justifications: • Belief changes should be resolved with as few agents as possible • Changing as few beliefs as possible When invoked: • Unlabels data • Chooses labeling for unlabelled shared data • Initiates labeling

  43. 7. Market Mechanisms For large or unknown # of agents • The goods being traded • Consumer agents that are trading the goods • Producer agents, with their technology for transforming some goods into others • Bidding & trading behaviors of agents

  44. Competitive Equilibrium • Consumers bid to maximize their utility, subject to budget constraints • Producers bid to maximize their profits, subject to technological capabilities • Net demand is zero for all goods Rational action: maximizes preferences for an agent (including past commitments)

  45. Societies of agents • Intelligent agents work well in groups (societies) not in isolation • Distributed system is a better solution • Peer to peer better than client server Social commitments: commitments of an agent to another

  46. Social dependence Social dependence (x y a p): Agent x depends on agent y with regard to act a for realizing state p, when p is a goal of x and x is unable to realize p while y is able to do so.

  47. Types of dependencies • Voluntary: agents adopt roles that bind them to certain commitments • Compound: mutual dependence occurs when x and y depend on each other for realizing a common goal p • Reciprocal: x and y depend on each other for realizing different goals

  48. Co-operation Form of mutual dependence Agents form a co-operative team when: • All agents share a common goal • Each agent is required to do its share to achieve the common goal by the group itself or a subgroup • Each agent adopts a request to do its share

  49. Conclusion • Characteristics of multi-agent systems. • Mechanisms for agents communication. • High level agent interaction protocols. • Societies of agents

  50. Future work To develop protocols or societies in which the effects of deception and misinformation can be constrained

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