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AOSE

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Title: AOSE


1
AOSE
  • Advanced Software Engineering
  • University College Dublin
  • December 2007
  • Dr Rem Collier

2
AOSE
  • Coordination

3
Coordination
  • The process by which an agent reasons about its
    local actions and the (anticipated) actions of
    others to try and ensure that the community acts
    in a coherent manner.

Nick Jennings,1996
4
The Coordination Problem
  • Managing the interdependencies between the
    activities of agents. e.g.
  • You and I both want to leave the room.
  • We independently walk towards the door, which can
    only fit one of us.
  • I graciously permit you to leave first.

5
Coordination
  • Coordination is a key concept in the design and
    implementation of complex dynamic systems
  • Its about managing dependencies between
    activities
  • This implies that every instance of coordination
    includes agents performing activities that are
    interdependent
  • Coordination is the process of building programs
    by gluing together active entities (such as
    processes, objects with threads, agents or whole
    applications) and determining how they interact!
  • Programming Computation Coordination

6
Why Coordinate?
  • Preventing anarchy or chaos
  • Dependencies between agents actions.
  • Need to meet global constraints
  • No individual has sufficient competence,
    resources or information to solve the entire
    problem.
  • Efficiency

7
Coordination Example
  • Consider an interaction between two robots, A and
    B, operating in a warehouse.
  • Each robot has been designed a different
    manufacturer.
  • They both have the capability to stack and
    unstack boxes that contain goods that have been
    stored in the building.
  • Because both robots work concurrently, they need
    to coordinate their actions to share the work
    load and to avoid knocking into each other and
    dropping the boxes.

8
How to Coordinate?
  • There are two basic ways of achieving this
  • Task sharing
  • When a problem isdecomposed intosubproblems
    andallocated to differentagents.
  • Result sharing
  • When agents shareinformation relevantto their
    subproblems.

Task 1
Task 1.2
Task 1.3
Task 1.1
9
How to Coordinate?
  • Task Sharing Example
  • Our warehouse agents agree a distribution of work
    and then go about that work.
  • Robot A works on the east side of the building.
  • Robot B works on the west side.
  • Result Sharing Example
  • Agents keep each other informed of their current
    activities and decide what to do independently.
  • Robot A decides to move box number A10456.
  • Robot A tells robot B.
  • Using this additional information, robot B
    independently decides to move another box A20987.

10
Task Sharing
  • The agent decomposes the task into a set of
    sub-tasks that are assigned dynamically to the
    agents at run-time.
  • Key Steps
  • Problem decomposition for distribution
  • Synthesis of sub-problem results to obtain the
    solution
  • Optimisation of the problem-solving activities of
    the agents
  • Techniques for the coordination of the agents
    activities
  • Example Technique Contract Net Protocol

11
Task Sharing Process
1. Problem decomposition
2. Subproblem solution
3. Answer synthesis
Ref Smith Davis, 1980
12
The Contract Net Protocol
I have a problem!
manager
Potential contrators
announcement
(b) Task Announcement
(a) Recognising the problem
manager
manager
Potential contrator
Award task
bids
(c) Bidding
(d) Award Contract
13
The Contract Net Protocol
14
..Task Allocation
  • A key problem is how to allocate the sub-tasks to
    the most appropriate set of agents

15
Result Sharing
  • Problem solving proceeds by agents cooperatively
    exchanging information as the solution is
    developed.
  • The set of tasks are pre-assigned at design time
  • Results may be shared
  • proactively - one agent sends another agent some
    information because it believes that the other
    will be interested in it.
  • reactively an agent sends information to
    another in response to a request.

16
Question
  • Traffic Management
  • I have a community of agents that are monitoring
    the level of traffic on a road network.
  • Individual agents are responsible for pre-defined
    area of the road network.
  • When an agent detects a build up of traffic in
    its area, it contacts a pre-assigned traffic
    management agent.
  • Mobile Computing
  • A personal agent (located on a users PDA)
    requests a map centred around the users
    coordinates that shows nearby hotels.
  • The map request is sent to a pre-assigned
    map-broker agent who then contacts an appropriate
    map agent to get the basic map and an
    appropriate restaurant agent to get a list of
    nearby restaurants and their coordinates.
  • Are these examples of coordination? If so, what
    type?

17
Issues in Coordination
  • Network Coherence Maximising how well a
    distributed system of agents work together.
  • Task and Resource allocation amongst agents.
  • Recognising and Resolving disparities or
    conflicts in goals, facts, beliefs, viewpoints,
    and behaviour of agents.
  • Determining the organisational structure of the
    agent system (i.e. the roles, responsibilities
    and permissions of agent in the system).

18
Coordination Techniques
  • Organisational Structures
  • Meta-level Information Exchange
  • e.g. Partial Global Planning (PGP), (Durfee)
  • Multi-agent Planning
  • Other Approaches
  • Norms and social laws
  • Joint Intentions

19
AOSE
  • Organisational Structures

20
Organisational Structures
  • A pattern of information and control
    relationships between individuals.
  • Responsible for shaping the types of interactions
    among the agents.
  • Aids coordination by specifying which actions an
    agent will undertake.
  • Organisational Patterns (Dignum Dignum, 2001)
  • Market
  • Network
  • Hierarchy

21
The Market Pattern
  • Goal Facilitate exchange between self-interested
    agents.
  • Agents are heterogenous and represent a diverse
    set of services and/or competencies.
  • Agents compete to perform tasks leading to their
    satisfaction of their own objectives.
  • Interaction occurs through communication and
    negotiation.
  • Negotiation rules are normally fixed (e.g. a
    particular auction protocol must be used).
  • Payoff is immediate.
  • Well suited to open-systems, this pattern has
    been used to model e-commerce scenarios and
    virtual enterprises.

22
The Market Pattern
  • Key Infrastructure Agent Roles
  • Identification.
  • registration of society members.
  • Matchmaker.
  • keeps track of needs and services of agents in
    system.
  • mediates in matching of demand and supply of
    goods or services.
  • Banking.
  • define ways to exchange goods and determine
    profit and fairness of exchanges.

23
The Hierarchy Pattern
  • Goal Coordinate the flow of resources or
    information by controlling and directing it via
    some (management) central point.
  • Each agent controls a statically defines
    sub-hierarchy (possibly empty).
  • Agents at lower levels in the hierarchy are
    dependent on agents at higher levels in the
    hierarchy.
  • Interactions are determined at design time, and
    are hardcoded into the system implementation.
  • Manager agents are responsible for controling,
    coordinating, and optimising sub-system
    activities.
  • Well suited to closed systems, this pattern has
    been used in information agents and management of
    communication networks.

24
The Hierarchy Pattern
  • Key Infrastructure Agent Roles
  • Controller.
  • Monitor and orient the overall performance of the
    (sub-) system.
  • Interface Agents.
  • Responsible for communication between the system
    and the outside world.

25
The Network Pattern
  • Goal Facilitate collaboration between
    self-interested agents that have a mutual goal.
  • Agents are willing to trade freedom in exchange
    for guarantees regarding security and
    trustworthiness.
  • Services may be traded for soft rewards such as
    increase in prestige.
  • Relationships are dependent on clear
    communication patterns and social norms.
  • Coordination is achieves through mutual interest,
    possibly via trusted third parties.
  • Coordination is governed by well-defined rules
    and sanctions.
  • Well suited to open systems in which security and
    trust are essential.

26
The Market Pattern
  • Key Infrastructure Agent Roles
  • Matchmaker
  • keeps track of needs and services of agents in
    system.
  • Mediates in matching of demand and supply of
    goods or services.
  • Gatekeeper
  • responsible for accepting and introducing new
    agents to the market.
  • informs new agents of the possibilities and
    capabilities of the market.
  • Notary
  • registers collaboration contracts between agents.
  • Monitoring Agents
  • Trusted third parties that keep track of the
    execution of collaboration contracts.

27
Example
  • The Automobile industry
  • Has a set of goals To produce different lines of
    cars
  • Has a set of agents to perform the tasks
    designers, engineers, salesmen
  • Possible Patterns (Malone, 1987)
  • Product Hierarchy
  • Functional Hierarchy
  • Centralised Market
  • Decentralised Market

28
Organisational Structures
  • Product Hierarchy

29
Organisational Structures
  • Functional Hierarchy

Product Manager (several products)
30
Organisational Structures
  • Centralised Market

Product Manager 3
Product Manager 2
Product Manager 1
Functional Managers
31
Organisational Structures
  • Decentralised Market

Product Manager 3
Product Manager 2
Product Manager 1
Designers
Salesmen
Engineers
32
Comparison
33
Organizational Structures
  • Organisational structures can be used to
    introduce clear lines of communication between
    the agents that exist within the system.
  • Advantages
  • Improved Efficiency.
  • Borrows from human society in which coordination
    has been successfully achieved...
  • Disadvantages
  • Reduced reliability (single points of failure).
  • Reduced flexibility (fixed structure).

34
AOSE
  • Meta-level Information Exchange

35
Meta-level Information Exchange
  • Exchange control level information about current
    priorities and focus.
  • Control level information
  • May change
  • Influence the decisions of agents
  • Does not specify which goals an agent will or
    will not consider.
  • Imprecise
  • Medium term can only commit to goals for a
    limited amount of time.

36
Partial Global Planning
  • Main principle cooperating agents exchange
    information in order to reach common conclusions
    about the problem solving process.
  • Why is planning partial?
  • The system does not generate a plan for the
    entire problem.
  • Why is planning global?
  • Agents form non-local plans by exchanging local
    plans and cooperating to achieve a non-local view
    of problem solving.

37
Partial Global Planning
  • Starts with the premise that goals are inherently
    decomposed.
  • Assumes that an agent with a goal to plan for
    might be unaware as to what goals other agents
    might be planning for and how those goals are
    related to its own.
  • Individual agents are not necessarily aware of
    the global system state.
  • Purpose of coordination is to develop sufficient
    awareness.

38
Partial Global Planning
  • Partial Global Planning involves 3 iterated
    stages
  • Each agent decides what its own goals are and
    generates short-term plans in order to achieve
    them.
  • Agents exchange information to determine where
    plans and goals interact.
  • Agents alter local plans in order to better
    coordinate their own activities.

39
Partial Global Planning
  • Partial Global Plan a cooperatively generated
    datastructure containing the actions and
    interactions of a group of agents.
  • Contains
  • Objective the larger goal of the system.
  • Activity map what agents are actually doing and
    the results generated by the activities.
  • Solution construction graph a representation of
    how the agents ought to interact in order to
    successfully generate a solution.

40
Example
  • Distributed Vehicle Monitoring Testbed (DVMT).
  • Aims to successfully track a number of vehicles
    that pass within the range of a set of
    distributed sensors (agents).
  • Each agent monitors a dedicated area
  • There could beoverlapping areas

41
AOSE
  • Multi-Agent Planning

42
Multi-Agent Planning
  • Agents generate, exchange and synchronise
    explicit plans of actions to coordinate their
    joint activity.
  • They arrange apriori precisely which tasks each
    agent will take on.
  • Plans specify a sequence of actions for each
    agent.
  • It is a trade-off between specificity and
    reactivity.

43
Multi-Agent Planning Techniques
  • Centralised Planning
  • Plans of individual agents analysed by a central
    coordinator to identify interactions.
  • Coordinator maintains a single global plan.
  • Minimizes the potential for conflict
  • Distributed Planning
  • Agents pass individual plans and check for
    coordination opportunities.
  • Each agent maintains and manages its own plan.
  • No global view conflict can occur

44
Multi-Agent Planning Example
  • e.g. Air traffic control domain (Cammarata)
  • Aim Enable each aircraft to maintain a flight
    plan that will maintain a safe distance with all
    aircrafts in its vicinity.
  • Each aircraft send a central coordinator
    information about its intended actions.
  • The coordinator builds a plan which specifies all
    of the agents actions including the ones that
    they should take to avoid collision.
  • What if we used a distributed planning approach?

45
Multi-Agent Planning
  • Critique
  • Agents share and process a huge amount of
    information.
  • Requires lots of computing and communication
    resources.
  • Centralised approaches introduce a single point
    of failure.
  • Sometimes Plans can also become obsolete very
    quickly

46
AOSE
  • Negotiation

47
Negotiation
  • The process of several agents searching for an
    agreemente.g. about price.
  • Reaching consensus

Rules of Encouter by Rosenchein and Zlotskin,
1994
48
Auctions
  • An Auction takes place between an auctioneer and
    a collection of bidders.
  • Goal is for the auctioneer to allocate the goods
    to one of the bidders.
  • In most settings, the auctioneer desires to
    maximise the price bidders desire to minimise
    the price.

49
..Selecting a Bid
50
Auction Parameters
51
English Auctions
  • English auctions are
  • First price
  • Open cry
  • Ascending
  • Dominant strategy successively bid a small
    amount more than the highest current bid until it
    reaches the valuation, then withdraw.
  • Susceptible to Winners curse
  • Winner is the one who overvalues the goods on
    offer and may end up paying more than its worth.

52
English Auctions
53
Dutch Auctions
  • Dutch auctions are
  • Open cry
  • Descending
  • Auctioneer starts at an artificially high price.
  • Then continually lowers the offer price until an
    agent makes a bid which is equal to the current
    offer price.
  • Dominant strategy None
  • Susceptible to Winners curse

54
Dutch Auctions
55
First-price Sealed-bid Auctions
  • One shot auction
  • Single round, where bidders submit a sealed-bid
    for the good.
  • Good is awarded to agent that made the highest
    bid.
  • Winner pays price of highest bid.
  • Best strategy bid less than true value.

56
Vickrey Auctions
  • Vickrey auctions are
  • second-price
  • sealed-bids
  • Goods are awarded to agent that made the highest
    bid.
  • Winner pays price of second highest bid.
  • Best strategy bid the true value.
  • Susceptible to anti-social behaviour

57
Lies and Collusions
  • Lies
  • By the bidders (e.g. In Vickrey auctions)
  • By the auctioneer (shills, in Vickrey auction)
  • Collusion of bidders
  • Coalition of bidders where they agree beforehand
    to put forward artificially low bids for the good
    on offer.
  • When the good is obtained, the bidders can then
    get the true value of the good and share the
    profits.

58
Towards Negotiation
  • Auctions have a number of limitations
  • Only concerned with the allocation of goods
  • Not adequate for settling agreements that
    concerns matters of mutual interest.
  • Negotiation covers far more than this!
  • It may involve
  • Exchange of information
  • Relaxation of initial goals
  • Mutual concession

59
Negotiation Example 1
  • Consider two companies A and B decide to form an
    alliance to develop a software product for the
    shipbuilding industry.
  • Company A has the shipbuilding market and
    knowledge in that domain.
  • Company B is a software company that specialises
    in CAD systems and CAE.
  • They negotiate to agree upon
  • the financial assets,
  • the skills and technology contributed by each
    company,
  • how much of the new product each company will
    own, and
  • who will market the product and provide
    first-line support for the product.

60
Negotiation Example 2
  • Consider two agents, each controlling a
    telecommunications network with associated
    resources such as
  • communication lines,
  • microwave links,
  • routing computers, and
  • short and long-term storage devices.
  • The load that each agent has to handle varies
    over time.
  • The agents negotiate about resource sharing.

61
Mechanisms, Protocols, Strategies
  • Negotiation is governed by a mechanism or a
    protocol
  • defines the rules of encounter between the
    agents
  • the public rules by which the agents will come to
    agreements.
  • Given a particular protocol, how can a particular
    strategy be designed that individual agents can
    use?

62
Mechanisms Design
  • Mechanism design is the design of protocols for
    governing multi-agent interactions.
  • Desirable properties of mechanisms are
  • Convergence/guaranteed success
  • Maximising social welfare
  • Pareto efficiency
  • Individual rationality
  • Stability
  • Simplicity
  • Distribution

63
Negotiation Components
  • Any negotiation setting will have 4 components
  • Negotiation set represents the space of possible
    proposals that agents can make
  • Protocol defines the legal proposals that agents
    can make
  • Collection of strategies (one for each agent)
    determines what proposals the agent will make
  • Rule to determine when an agreement has been
    reached

64
Negotiation Process 1
  • Negotiation usually proceeds in a series of
    rounds, with every agent making a proposal at
    every round.
  • Communication during negotiation

65
Negotiation Process 2
  • Another way of looking at the negotiation process
    is

66
Complexity of Negotiations
  • Some attributes that make the negotiation process
    complex are
  • Multiple attributes
  • Single attribute (price) symmetric scenario.
  • Multiple attributes several inter-related
    attributes, e.g. buying a car.
  • The number of agents and the way they interact
  • One-to-one, e.g. single buyer and single seller.
  • Many-to-one, e.g. multiple buyers and a single
    seller, auctions.
  • Many-to-many, e.g. multiple buyers and multiple
    sellers.

67
Monotonic Concession Protocol
  • Negotiation proceeds in rounds
  • On round 1, agents simultaneously propose a deal
    from the negotiation set.
  • Agreement is reached if one agent finds that the
    deal proposed by the other agent is at least as
    good or better than its proposal.

68
Monotonic Concession Protocol
  • If no agreement is reached, then negotiation
    proceeds to another round of simultaneous
    proposals.
  • In round u1, no agent is allowed to make a
    proposal that is less preferred by the other
    agent than the deal proposed at time u.
  • If neither agent concedes, then negotiation
    terminates with a conflict deal.

69
Monotonic Concession Protocol
  • Advantages
  • Symmetrically distributed (no agent plays a
    special role)
  • Ensures convergence
  • It will not go on indefinitely
  • Disadvantages
  • Agents can run into conflicts
  • Inefficient no quarantee that an agreement will
    be reached quickly

70
Key Questions
  • 3 key questions to be answered
  • What should an agents first proposal be?Its
    most preferred deal.
  • On any given round, who should concede?The agent
    least willing to risk conflict.
  • If an agent concedes, then how much should it
    concede?Just enough to change the balance of
    risk.

71
The Risk Factor
  • One way to think about which agent should concede
    is to consider how much each has to loose by
    running into conflict at that point.

Maximum loss from conflict
How much am I willing to risk a conflict?
Maximum loss from concession
Conflict deal
Ai best deal
Aj best deal
72
The Zeuthen Strategy
  • Uses the risk evaluation strategy
  • Suppose you have conceded a lot. Then
  • Your proposal is now close to conflict deal.
  • You are more willing to risk conflict.
  • An agent will be more willing to risk conflict if
    the difference in utility between its current
    proposal and the conflict deal is low.
  • Degree of willingness to risk a conflict can be
    defined as
  • utility i loses by conceding and accepting js
    offerutility i loses by not conceding and
    causing conflict

Riskti
73
About MCP and Zeuthen Strategies
  • Advantages
  • Simple and reflects the way human negotiations
    work.
  • Stability in Nash equilibrium if one agent is
    using the strategy, then the other can do no
    better than using it him/herself.
  • Disadvantages
  • Computationally expensive players need to
    compute the entire negotiation set.
  • Communication burden negotiation process may
    involve several steps.

74
Summary
  • Agent Communication Languages make coordination
    and negotiation possible.
  • Coordination is about managing the
    interdependencies between the activities of the
    agents.
  • Negotiation is about reaching a consensus between
    agents.
  • These techniques provide a basis for allowing
    agents to dynamically cooperate and collaborate
    in order to achieve tasks that are beyond their
    individual capabilities.
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