Agent-based E-commerce System

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Agent-basedE-commerce System

• Maria Ganzha
• Marcin Paprzycki
• http//agentlab.swps.edu.pl

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Agent-basedE-commerce System

• 1. Introduction

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Assumptions

• Modelling a distributed marketplace ? Internet
• e-buyers visit e-shops with a desire to purchase
  products
• buyers negotiate prices with sellers
• clients decide which store to buy from
• wholesalers provide products for e-shops
• Utilizing software agents for all e-commerce
  functions
• develop complete system skeleton ? all agent
  functions and agent interactions implemented

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Use case of the system
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What's different (1)

• Multiple items of a product placed for sale one
  after another ?? series of price negotiations
• Multiple items sold ? price negotiations are
  organized differently ? discrete process
• Buyer Agents (BA) collected and released in
  groups to participate in negotiations
• while negotiation takes place BAs communicate
  only with the Seller Agent (SeA)
• meanwhile next group of BAs is collected (as
  they arrive) and will participate in the next
  negotiation

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What's different (2)

• Multiple subsequent auctions (involving items of
  the same product) take place ? price negotiation
  mechanism can change
• Model of a complete e-commerce system
• actions that take place before negotiations
• actions that take place after negotiations
• product logistics
• Clients choose shop from which to make a purchase
  ? airline reservation model

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Agent-basedE-commerce System

• 2. Ontologies and their utilization

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Ontology of products (1)

• Product taxonomy inspired by the Global Products
  Classification (GPC) standards
• shoes
• cameras
• Product skeleton
• created by sub-classing the base ontology
• shoes of the same style and brand
• Product variation
• instance of a product skeleton
• shoes of given style and brand of a particular
  size and colour

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Ontology of products

• Instance

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Ontology of products (2)
hasBrand a owlDatatypeProperty
rdfsdomain Product rdfsrange xsdstring
. hasColor a owlObjectProperty
rdfsdomain Product rdfsrange Color
. hasSize a owlObjectProperty rdfsdomain
Product rdfsrange Size .

• Product
• a owlClass .
• Clothing
• rdfssubClassOf Product .
• Shoes
• rdfssubClassOf Clothing .
• ShoesWithLaces
• rdfssubClassOf Shoes .
• AthleticShoes
• rdfssubClassOf Shoes .
• hasPrice
• a owlObjectProperty
• rdfsdomain Product
• rdfsrange Price .

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Ontology of product instance (1)

• _at_prefix cc lthttp//www.ibspan.waw.pl/e-cap/produc
  t/clothing-catalog.owlgt
• _at_prefix prod lthttp//www.ibspan.waw.pl/e-cap/prod
  uct/product.owlgt .
• _at_prefix lthttp//www.ibspan.waw.pl/e-cap/db/cic/p
  roducts.owlgt .
• Product1165510834375 a ccProtectiveLowerBodyWea
  rBrick,
• a prodProductEntity
• cchasConsumerLifestage ccUnclassified
• cchasGender ccFemale
• cchasIfDisposable ccYes
• cchasSafetyFeatures ccColdResistant
• cchasTypeOfMaterial ccCombination
• cchasTypeOfProtectiveLowerBodyWear
  ccProtectiveKneePads

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Ontology of product instance (2)

• _at_prefix avc lthttp//www.ibspan.waw.pl/e-cap/produ
  ct/audio-visual-catalog.owlgt .
• _at_prefix prod lthttp//www.ibspan.waw.pl/e-cap/prod
  uct/product.owlgt .
• _at_prefix lthttp//www.ibspan.waw.pl/e-cap/db/cic/p
  roducts.owlgt .
• Product1165506706750 a avcTelevisions_Hand_Held
  Brick,
• prodProductEntity
• avchasColourFormat avcBlack_White
• avchasTypeOfTelevisions avcPlasma
• avchasIfWithRadio avcYes
• avchasScreenSize avc_2.5Inch .

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Ontology of products

• Instance

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Product registration (1)

• SA registers sold products with the CIC using ACL
  REQUEST messages
• message content specified using FIPA Semantic
  Language (FIPA SL)
• FIPA SL term representing an action has the form
  
• (action Agent Action)
• Specifically
• Agent the agent performing the action
• Action the action which is to be performed

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Product registration (2)

• Agent CIC
• (agent-identifier
• name cic_at_ibspan.waw.pl
• addresses http//www.ibspan.waw.pl9999)
• Action register set of products sold by a SA
• (Add-Product-Shop
• (Entry
• product (set PD1 ... PDn)
• shop Shop
• gatekeeper Gatekeeper))
• PDi product descriptions in OWL (Lite) ?
  ontology instance
• (ProductDescription
• language "owl"
• description OWL-EXPRESSION )

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Product registration (3)

• Products that are sold have to be registered with
  the CIC
• Product ID
• extension of product ontology to specify that a
  given shop sells a given product
• shop identified by its Gatekeeper Agent (GA)
• GA-1 a gatekeeperAgent
• name ga509_at_ibspan.waw.pl
• addresses http//www.ibspan.waw.pl9999
• shop 767
• sells Product4094094049.

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Usage scenario

• System is running for some time
• SAs have registered their products with the CIC
• stored in a Jena repository
• middleware over a database to manage stored in
  the system instances of ontologies
• CAs know where the CIC is
• CAs have interacted with some SAs
• SAs have interacted with some CAs
• Scenario ? what happens when user wants to buy a
  pair of athletic shoes
• assumption ? user interacts with its CA through a
  web-based interface

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Processing User Request

• A query-string (URL extension) representing user
  request reaches the CA
• Example
• ?productClassAthleticShoes
• hasColorBlackColorprizeofCurrencyEUR
• prizevalueleftBound25prizevaluerightBound5
  0
• sizevalue136sizevalue137
• CA translates query-string into a SPARQL query
• SPARQL rather than RDQL because
• SPARQL is more expressive than RDQL
• SPARQL is about to obtain standardization
• JENA already includes working SPARQL module
• SPARQL query engine is better tested

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SPARQL Query example

• PREFIX my
• lthttp//jacs.ibspan.waw.pl/ontologygt
• SELECT ?product, ?gateway
• ?gateway sells ?product
• ?product,
• rdfssubClassOf myAthleticShoe
• myhasColor myBlackColor
• myhasPrize ?prize
• myhasSize ?size
• ?prize,
• myofCurrency myEUR
• myvalue ?prizeValue
• ?size myvalue ?sizeValue ,
• FILTER
• ((?sizeValue 36.0 ?sizeValue 37.0)
• (?prizeValue gt 25.0 ?prizeValue lt 50.0))

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CIC result set and what next?

• CA packs the SPARQL query into an ACL QUERY-REF
  message send to CIC agent
• CIC returns a (possibly empty) set of answers
  packed in an ACL INFORM message containing
  expressions like this
• (set
• (sequence PD1 GA1) ...
• (sequence PDn GAn))
• CA evaluates this list based on trust/image
• Based on results of evaluation CA will interact
  with selected e-shops

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Before Negotiation
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Before Price Negotiations

• CA asks the GA about admission rules
• GA checks CA-trust product availability and
  responds
• no more product
• go away ? we do not trust you
• BAs have to come
• CA creates and sends a BA
• BAs created locally
• RESULT ? BA skeleton is in
• GA provides BA with negotiation details
• BA requests strategy (for THAT negotiation)
• RESULT ? BA is ready and informs the GA

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Modular Agents
?
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Negotiation and After

• GA manages a pool of SeAs
• when the time comes, it releases the list of BAs
  to a free and appropriately configured SeA for
  negotiation
• When negotiation is finished
• SeA informs winning BA and SA (via GA)
• SA (via SDA) determines for how long to reserve
  the product for the winner BA/CA
• depending on BA/CA image/trust
• SA informs the BA about the reservation
  conditions
• BA informs its CA about results on negotiation

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Decision Time

• CA receives ACL INFORM messages from its BAs
• inform about winning or loosing negotiations
• come completely asynchronous
• varying time of reservation
• CA utilizes multicriterial analysis to decide
• to make purchase utilizing an available offer
• to try for a better price
• to abandon purchase

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Agent-basedE-commerce System

• 3. Trust in the system

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Trust and Image

• trust standard conceptualization
• a peers belief in another peers capabilities,
  honesty and reliability based on its own direct
  experiences
• trust in our system
• fulfilment of a contract
• product matching our order
• delivery time
• reliability of the buyer
• image involves perceptions
• given shop is cheap or expensive

And I could afford to buy at your shop
But your prices are too high for me...
I also trust you. I believe in your honesty.
I trust you. I believe in your responsibility.
Costin.Client
Pawel.Client
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Trust in the System
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Client Trust

• Most processes that can visibly change trust in a
  given store take place during Sale finalization
• involves, among others, payment and delivery of
  products

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Initial Trust Sequence Diagram
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Shop Trust

• Most of process which can visibly change trust
  take place during After-negotiation period
• SA create reservation
• BA
• confirm purchase
• reject purchase (?time?)
• no answer/answer after deadline

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Modelling Trust
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Effect of a
Brave client
I want to buy new shoes and I'm gonna try to
negotiate with Maria's and Marcin's shops.
Tn(Maria)0
Tn(Marcin)0
T
Maciej.Client
Careful merchant
You must be really obnoxious to make me angry,
but as soon you managed to do it, I won't change
my opinion about you so fast.
a0.1
Tn(Maciej)0
Radical merchant
I can be really mad, when you make me angry, but
I also forget about negative behaviours quickly.
Tn(Maciej)0
a0.8
Marcin.Merchant
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TA(e) How Can It Look Like

• Reservation time is tres, no-penalty time is
  tnop, reservation cancellation time is tcant
• BA has finalized purchase at time t ?
  0,tres?TA(e) 1
• BA has cancelled reservation at time
  tcan?0,tnop ? TA(e) 0
• BA has cancelled reservation at time tcan ?
  (tnop, tres. Let us assume that the maximum
  penalty for cancellation at time tcan tres is
  ?, where 0  ? a, and the TA(e) is linear
  function, then TA(e) a tcan b, where a ? /
  (tres tnop) and b ? tnop /(tres tnop)
• if BA has not responded in time t tres, then
  TA(e) a

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Comments

• Trust value as a part of CA's strategy
• it will buy one item, while has multiple
  reservations
• which to reject imediately?
• which can expire?
• where not to send agent back to negotiations?
• etc.
• knowing that over time good and bad behaviors are
  being forgotten and the incoming agent is treated
  as unknown

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Agent-basedE-commerce System

• 4. Price negotiations

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Price Negotiation Overview

• BJP framework
• negotiation participants
• host ? negotiation manager
• buyer(s)
• seller(s)
• negotiation process has phases
• proposal submission
• agreement formation
• Our system
• admission to negotiations Gatekeeper agent (GA)
  not a part of negotiations
• rules for admission to negotiations outside of
  the host

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Negotiation Host Structured Into Subagents
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Negotiation Rules

• Enforce specific negotiation mechanism
• for checking the validity of negotiation
  proposals ProposalValidator
• for protocol enforcement ProposalEnforcer
• for updating the negotiation status and informing
  participants InformationUpdater
• for agreement formation AgreementMaker
• for controlling the negotiation termination
  NegotiationTerminator

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English Auction

• single-item
• ?rst-price
• open-cry
• ascending auctions
• single seller and many buyers
• time limit for ending the auction
• seller reservation price
• simple, well-known, !uninteresting!

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Posting Rule

• IF
• There is a valid proposal Pr submitted by a
  participant with role Buyer on product A
• AND
• There is an active proposal submitted by a
  participant with role Seller on product A
• THEN
• Proposal Pr is posted

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JESS representedrule
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Dutch Auction

• Single item Dutch auction
• Seller begins with a high asking price which is
  lowered until buyer is willing to accept the
  price, or a predetermined minimum price is
  reached (no sale)
• Multiple-item Dutch auction??

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Dutch Auction Scenario (1)

• Participants
• Negotiation Host (location where the
  negotiations takes place)
• Single Seller Agent (SeA)
• Multiple Buyer Agents (BA)s
• N units of product P are to be sold
• Initial bid posted on the Blackboard

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Dutch Auction Scenario (2)

• SeA subsequently reduces the price
• One of BAs (e.g. BA5) responds with an ACL
  message informing that it is ready to purchase M,
  M N, units of P at a price equal to the current
  bid
• then number of available units is reduced by M
  and BA5 is removed from negotiations (each BA is
  allowed to submit at most one successful bid)
• Process continues until (1) all N units are sold,
  or (2) minimal price of the SeA is reached, or
  (3) time of inactivity is over

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Seller Rules

• Seller is allowed to shout a new price when one
  of the following conditions holds
• it is the ?rst shout
• one of Buyers submitted a bid that was successful
• no successful bids were received and at least Tm
  time units elapsed since the last shout

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Improvement-Seller Rule

• IF
• participant with role Seller has posted
  proposal Pr
• and
• value of last offer posted by Seller is B
• and
• minimum decrement is H
• and
• X(Pr) B - H
• THEN
• proposal Pr is active

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Experiments

• JADE agent environment
• JAVA Expert System Shell (JESS)
• up to 20 machines in a single network
• homogeneous environment (Windows or Linux)
• heterogeneous environment (Windows Linux)
• system is being re-implemented, so next slides
  represent what was (IT WORKED)

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Agent-basedE-commerce System

• 6. Logistics

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Logistics

• SDA controls supply and demand information
• SDA sends product level prediction for a
  time-period (i.e. weekly prediction for 5 weeks)
• WA analyses the status of the warehouse and
  decides how many to buy
• Order (if necessary) is send to the Logistics
  Agent (LA)
• LA utilizes a pool for Ordering Agents to process
  and order

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Use Case of Logistics
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END of Agent-basedE-commerce System