AOSE

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AOSE

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

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AOSE

• Coordination

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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
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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.

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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

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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

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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.

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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
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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.

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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

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Task Sharing Process
1. Problem decomposition
2. Subproblem solution
3. Answer synthesis
Ref Smith Davis, 1980
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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
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The Contract Net Protocol
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..Task Allocation

• A key problem is how to allocate the sub-tasks to
  the most appropriate set of agents

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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.

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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?

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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).

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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

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AOSE

• Organisational Structures

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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

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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.

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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.

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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.

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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.

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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.

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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.

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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

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Organisational Structures

• Product Hierarchy

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Organisational Structures

• Functional Hierarchy

Product Manager (several products)
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Organisational Structures

• Centralised Market

Product Manager 3
Product Manager 2
Product Manager 1
Functional Managers
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Organisational Structures

• Decentralised Market

Product Manager 3
Product Manager 2
Product Manager 1
Designers
Salesmen
Engineers
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Comparison
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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).

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AOSE

• Meta-level Information Exchange

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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.

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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.

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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.

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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.

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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.

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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

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AOSE

• Multi-Agent Planning

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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.

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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

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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?

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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

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AOSE

• Negotiation

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Negotiation

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

Rules of Encouter by Rosenchein and Zlotskin,
1994
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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.

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..Selecting a Bid
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Auction Parameters
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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.

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English Auctions
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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

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Dutch Auctions
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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.

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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

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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.

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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

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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.

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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.

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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?

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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

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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

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Negotiation Process 1

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

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Negotiation Process 2

• Another way of looking at the negotiation process
  is

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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.

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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.

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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.

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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

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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.

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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
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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
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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.

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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.