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Automated Negotiation: Prospects, Methods and Challenges
N. R. Jennings1, P. Faratin2, A. R. Lomuscio3, S. Parsons4, C. Sierra5 and M. Wooldridge4
1 Dept. of Electronics and Computer Science, University of Southampton,Southampton SO17 1BJ, [email protected]
2 Dept. of Electronic Engineering, Queen Mary and Westfield College,University of London, London E1 4NS, UK.
3 Dept. of Computing, Imperial College of Science, Technology and Medicine,London SW7 2BZ, UK.
4 Dept. of Computer Science, University of Liverpool,Liverpool L69 7ZF, UK.
{s.d.parsons, m.j.wooldridge}@csc.liv.ac.uk
5 Artificial Intelligence Research Institute, Spanish Scientific Research Council,Campus UAB, 08193 Bellaterra, Barcelona, Spain.
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1. Introduction
An increasingnumberof computersystemsarebeingviewedin termsof autonomousagents.
Therearetwo maindriversto thistrend.Firstly,agentsarebeingadvocatedasanextgeneration
modelfor engineeringcomplex,distributedsystems[13], [44]. Secondly,agentsarebeingused
asan overarchingframeworkfor bringing togetherthe componentAI subdisciplinesthat are
necessaryto designandbuild intelligent entities[24], [32]. While thereis still muchdebate
abouttheprecisenatureof agenthood,anincreasingnumberof researchersfind thefollowing
characterisation useful [44]:
an agent is an encapsulatedcomputersystemthat is situatedin someenvironment
and that is capableof flexible, autonomousaction in that environmentin order to
meet its design objectives
Thereare a numberof points about this definition that requireelaboration.Agentsare: (i)
clearly identifiableproblemsolving entitieswith well-definedboundariesand interfaces;(ii)
situated(embedded)in a particularenvironment—they receive inputs relatedto the stateof
their environment throughsensorsand they act on the environment througheffectors; (iii)
designedto fulfill a specificpurpose—they have particularobjectives(goals)to achieve; (iv)
autonomous—they havecontrolbothover their internalstateandover theirown behaviour; (v)
capableof exhibiting flexible problemsolvingbehaviour in pursuitof theirdesignobjectives—
they needto bebothreactive (ableto respondin a timely fashionto changesthatoccurin their
environment) and proactive (able to act in anticipation of future goals) [45].
Whenadoptinganagent-orientedview of computation,it is readilyapparentthatmostproblems
requireor involvemultipleagents: to representthedecentralisednatureof theproblem,themul-
tiple loci of control, the multiple perspectivesand/orthe competinginterests[6]. Moreover,
theseagentswill needto interactwith oneanother, eitherto achieve their individual objectives
or to managethedependenciesthat follow from beingsituatedin a commonenvironment[7],
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[14]. Theseinteractionscanvary from simpleinformationinterchanges,to requestsfor partic-
ularactionsto beperformedandon to cooperation(working togetherto achieveacommonob-
jective)andcoordination(arrangingfor relatedactivitiesto beperformedin acoherentmanner).
However,perhapsthemostfundamentalandpowerfulmechanismfor managinginter-agentde-
pendenciesat run-timeis negotiation—theprocessby which a groupof agentscometo a mu-
tually acceptableagreementon somematter.Negotiationunderpinsattemptsto cooperateand
coordinate(bothbetweenartificial andhumanagents)andis requiredbothwhentheagentsare
self interestedandwhentheyarecooperative.It is socentralpreciselybecausetheagentsare
autonomous.Foranagentto influenceanacquaintance,theacquaintanceneedsto beconvinced
that it shouldact in a particularway.Themeansof achievingthis stateareto makeproposals,
tradeoptions,offer concessions,and(hopefully)cometo a mutuallyacceptableagreement.In
short, to negotiate.
Givenits ubiquityandimportancein manydifferentcontexts,negotiationtheoryincorporatesa
broadrangeof phenomenaandmakesuseof manydifferentapproaches(e.g.from AI, Social
PsychologyandGameTheory).Despitethis variety,however,automatednegotiationresearch
canbe consideredto dealwith threebroadtopics(see[21] for a moredetailedclassification
scheme):
• NegotiationProtocols: thesetof rulesthatgoverntheinteraction.Thiscoverstheper-
missibletypesof participants(e.g.thenegotiatorsandany relevant third parties),the
negotiationstates(e.g.acceptingbids,negotiationclosed),theeventsthatcausenego-
tiation statesto change(e.g.no morebidders,bid accepted)andthe valid actionsof
the participantsin particularstates(e.g. which messagescan be sentby whom, to
whom, at what stage).
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• Negotiation Objects: the rangeof issuesover which agreementmustbe reached.At
oneextreme,theobjectmaycontaina singleissue(suchasprice),while on theother
hand it may cover hundredsof issues(relatedto price, quality, timings, penalties,
termsandconditions,etc.).Orthogonalto theagreementstructure,anddeterminedby
the negotiationprotocol,is the issueof the typesof operationthat canbeperformed
on agreements.In the simplestcase,the structureandthe contentsof the agreement
arefixedandparticipantscaneitheracceptor rejectit (i.e. a take it or leave it offer).
At thenext level, participantshave theflexibility to changethevaluesof theissuesin
thenegotiationobject(i.e. they canmake counter-proposalsto ensurethe agreement
better fits their negotiation objectives). Finally, participantsmight be allowed to
dynamically alter (by adding or removing issues)the structureof the negotiation
object(e.g.a carsalesmanmayoffer oneyear’s free insurancein orderto clinch the
deal).
• Agents’ Decision Making Models: the decisionmaking apparatusthe participants
employ to actin line with thenegotiationprotocolin orderto achieve theirobjectives.
The sophisticationof the model, as well as the rangeof decisionsthat have to be
made,areinfluencedby theprotocolin place,by thenatureof thenegotiationobject,
and by the range of operations that can be performed on it.
Therelativeimportanceof thesethreetopicsvariesaccordingto thenegotiationandenviron-
mentalcontext.Thus,in somecircumstancesthenegotiationprotocolis thedominantconcern
(e.g.[33], [43]). For example,thesystemdesignermaydeterminethat thenegotiationis best
organisedusinga particularform of auction(e.g.English,Dutch,Vickrey, First-PriceSealed
Bid). This mechanismdesignchoiceconstrainsthe typesof operationsthatcanbeperformed
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on thenegotiationobject(no counter-proposalsor issueextensions)andprescribesthebehav-
iour of theagents’decisionmakingmodels(e.g.strategicbehaviouris pointlessandtheagents’
dominantstrategyis to simply bid up to their truereservationvalue).In othercases,however,
theagent’sdecisionmakingmodelis thedominantconcern(e.g.[37], [40]). Here,theprotocol
doesnotprescribeanoptimalstrategyfor theagentandthereis scopefor strategicreasoningto
determinethebestcourseof action.In suchcases,therelativesuccessof two agentsis deter-
mined by the effectivenessof their reasoningmodel—thebetter the model, the greaterthe
agent’s reward.
Given the wide variety of possibilities,it shouldbe clearthat thereis no universallybestap-
proachor techniquefor automatednegotiation.Rather,thereis aneclecticbagof methodswith
propertiesandperformancecharacteristicsthatvarysignificantlydependingon thenegotiation
context.Theaim of this paperis, therefore,to examinethespaceof negotiationopportunities
for autonomousagents,to identify andevaluatesomeof the key techniques,andto highlight
someof themajorchallengesfor futureautomatednegotiationresearch.Thispaperis notmeant
asa surveyof the field of automatednegotiation.Rather,thedescriptionsandassessmentsof
thevariousapproachesaregenerallyundertakenwith particularreferenceto work in which the
authorshavebeeninvolved. However,the specific issuesraisedshouldbe viewed as being
broadly applicable.
Theremainderof thispaperis structuredasfollows.Section2 presentsagenericframeworkfor
automatednegotiation.This frameworkis thenusedto structurethesubsequentdiscussionand
analysisof thevariousnegotiationtechniques;section3 dealswith gametheoretictechniques,
section4 with heuristictechniques,andsection5 with argumentation-basedtechniques.Finally,
section6 outlinessomeof themajorchallengesthatneedto beaddressedbeforeautomatedne-
gotiation becomes pervasive.
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2. A Generic Framework for Automated Negotiation
Negotiationcanbeviewedasadistributedsearchthroughaspaceof potentialagreements(fig-
ure1). Thedimensionalityandtopologyof this spaceis determinedby thestructureof thene-
gotiationobject.Indeed,onecouldconsidereachattributeof thenegotiationobjectto havea
separatedimensionassociatedwith it; clearly,in this view, thespaceof figure 1 concernstwo
attributes.Thus,whennewissuesareadded(or old onesremoved)duringthecourseof anego-
tiation, thenextradimensionsareadded(or removed)andthenumberof pointsof agreement
may increase(or decrease).Similarly, if an agentchangesoneof the valuesof oneof the at-
tributes within an offer, it is moving from one point in the agreement space to another.
Foragivennegotiation,theparticipantsaretheactivecomponentsthatdeterminethedirection
of thesearch.At thestartof this process,eachagenthasa portionof thespacein which it is
willing to makeagreements.Typically, it alsohassomemeansof ratingthepointsin its space
andsomemeansof usingthis ratingto determinetheactualagreementsit makes.Negotiation
proceedsby theparticipantssuggestingspecificpoints(or regions)in theagreementspaceas
potentiallyacceptable.During the negotiationprocess,the participants’agreementspaces(as
well astheir ratingfunctions)maychange:theymayexpand,contract,or shift, for examplebe-
causetheir environmentchangesor becausethey are persuadedto changetheir views. The
searchterminateswhentherequirednumberof participantsfind amutuallyacceptablepoint in
the agreementspaceor when the protocoldictatesthat the searchshouldbe terminated(for
whatever reason) without making an agreement.
Given this metaphor,figure 1 canbe seento representagentA1 negotiatingwith two other
agents(A2 andA3). Theagreementstructureis thesamein bothcases.Thecurrentoffer in the
A1-A3 negotiation(theseinteractionsarethelightly colouredexchanges)is in theareaof over-
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lapbetweenthetwo agentsmeaningthatit couldrepresentapotentialagreementbetweenthem.
Howeverthecurrentoffer in theA1-A2 negotiation(theseinteractionsarethedarkly coloured
exchanges)will not leadto anagreementsinceit is outsidetheagreementspaceof A2 (indeed
in thiscase,A1 andA2 currentlyhavenon-intersectingareasof agreementmeaningthatnodeal
is possible). For more on this metaphor for viewing the agreement space see [15], [20], [22].
Fromthis representation,it canbeseenthattheminimalnegotiationcapabilitiesare:(i) to pro-
posesomepartof theagreementspaceasbeingacceptable;and(ii) to respondtosuchaproposal
indicatingwhetherit is acceptable.In otherwords,theminimumrequirementof a negotiating
agentis theability to makeandrespondto proposals.Hereweconsideraproposalto beasolu-
tion to thenegotiationproblem;eithera singlecompleteproposedsolution,a singlepartialso-
lution, or a group of completeor partial solutions.In termsof the agreementspace,these
differentkindsof proposalsbecomeasinglepoint,aregionof thespace,asetof points,or aset
of regionsof thespace(for exampleapartialsolutionwouldbeanyregionof thespacein which
thequalitywasabovesomelevelandthepricebelowacertainthreshold).Generallyspeaking,
proposalscanbemadeeitherindependentlyof otheragents’proposalsor basedonthenegotia-
tion history.
Arguablythesimplestkind of negotiationwecanimagineis aDutchauction[31]. Theauction-
eer(oneagentin thenegotiation)callsout prices(negotiationobjectswith a singleattribute).
Whenthereis no signalof acceptancefrom theotherpartiesin theauction(otheragentsin the
negotiation)theauctioneermakesanewoffer which it believeswill bemoreacceptable(by re-
ducingtheprice).Here,becauseof theconvention(protocol)underwhichtheauctionoperates,
a lack of responseis sufficientfeedbackfor theauctioneerto infer a lack of acceptance.How-
everin anythingmorecomplexthanthis ratherspecialcase,theminimal requirementfor the
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“other agents”is that theyareableto indicatedissatisfactionwith proposalsthat theyfind un-
acceptable.
If agentscanonlyacceptor rejectothers’proposals,thennegotiation(andespeciallynegotiation
overobjectsthataremulti-dimensional)canbevery time consumingandinefficient sincethe
proposerhasnomeansof ascertainingwhy theproposalis unacceptable,norwhethertheagents
arecloseto anagreement,nor in which dimension/directionof theagreementspaceit should
movenext.Hencetheproposeris essentiallypickingpointsin theagreementspacebasedonits
perceptionof whatotherspreferandhopingthatit will eventuallystumbleuponsomethingac-
ceptable.To improvetheefficiencyof thenegotiationprocess,therecipientneedsto beableto
providemoreusefulfeedbackon theproposalsit receives.This feedbackcantaketheform of
a critique (commentson which partsof theproposaltheagentlikes or dislikes1) or a counter-
proposal(analternativeproposalgeneratedin responseto aproposal).Fromsuchfeedback,the
proposershouldbein a positionto generatea proposalthat is morelikely to leadto anagree-
ment (if it chooses to do so).
Considertheconceptof a critique first. A critiqueprovidestwo formsof feedback:(i) it sug-
gestsconstraintsonparticularnegotiationissuesand(ii) it indicatesacceptance/rejectionof par-
ticular parts of the proposal(or indeedof the whole proposal).To illustrate thesepoints,
consider the following short dialogues that are examples of proposals followed by critiques:
A: I propose that you provide me with service X under the following
conditions.
B: I am happy with the price of X, but the delivery date is too late.
1. To avoid introducing an unnecessarilylarge numberof different types of statement,we considersimple
accept/reject statements to be special cases of critiques.
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A: I propose that I will provide you with service Y if you provide me with
service X.
B: I don’t want service Y.
In thefirst case,thecritiqueindicatesthoseaspectsof theproposalthatareacceptableandthose
thatneedto bemodifiedandit alsosuggestsaconstraintononeof theissues(deliverydateear-
lier thanthecurrentsuggestion).In thesecondcase,thecritiqueindicatesoutrightrejectionof
partof theproposal.Generallyspeaking,themoreinformationplacedin thecritique,theeasier
it is for the original agent to determine the boundaries of its opponent’s agreement space.
Counter-proposalsarethesecondfeedbackmechanism.A counter-proposalis simplyapropos-
al thatis morefavourableto thesender,madein responseto apreviousproposal.Thefollowing
are examples of proposals followed by counter-proposals:
A: I propose that you provide me with service X.
B: I propose that I provide you with service X if you provide me with
service Z.
A: I propose that I provide you with service Y if you provide me with
service X.
B: I propose that I provide you with service X if you provide me with
service Z.
In the first case,the counter-proposalextendsthe initial proposal,and in the secondcaseit
amendspartof theinitial proposal.Counter-proposalsdiffer from critiquesin thatthefeedback
is lessexplicit (therecipientof a counter-proposalhasto infer theconstraintsandpreferences
from thewaytheproposalis re-constituted),butgenerallymoredetailed(sincespecificregions
of the opponent’s agreement space are identified).
On their own, proposals,critiques,andcounter-proposalsarebald statementsof what agents
want.Thus,their scopeis confinedsolelyto thestructureof thenegotiationobject.While it is
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perfectlypossibleto basenegotiationson just theseobject-levelconstructs(indeedthis is pre-
ciselywhatmostcurrentnegotiationmodelsdo),doingsodiminishessomeof thepotentialof
negotiation technology. For example, it means that agents cannot:
• Justify their negotiation stance;
An agentmighthaveacompellingreasonfor adoptingaparticularnegotiationstance.
For example,acompany maynotbelegally entitledto sellaparticulartypeof product
to a particulartypeof consumeror a particularitem maybeout of stockandthenext
delivery might not beuntil the following month.In suchcases,theability to provide
the justification for its attitudetowardsa particularissuecanallow the opponentto
more fully appreciate an agent’s constraints and behaviour.
• Persuade one another to change their negotiation stance;
Agentssometimesneedto actively changetheir opponents’agreementspace,or its
ratingover thatspace,in orderfor a dealto bepossible.In suchcases,agentsseekto
constructargumentsthat they believe will make their opponentlook morefavourably
upontheir proposal.Thus,argumentsseekto identify opportunitiesfor suchchange
(e.g.a car salesmanthrows in a stereowith a car to increasethe valueof the good),
createnew opportunitiesfor change(e.g.a carsalesmanaddsa new dimensionto the
rating function by highlighting the car’s novel securityfeatures)or modify existing
assessmentcriteria(e.g.carsalesmangetsthebuyerto changeits evaluationfunction
by convincing him that security is more important than high speed).
In bothcases,negotiatorsareprovidingargumentsto supporttheir stance(henceargumenta-
tion-basednegotiation). Thus,in additionto generatingproposals,counter-proposalsandcri-
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tiques,thenegotiatoris seekingto maketheproposalmoreattractive(acceptable)by providing
additionalmeta-levelinformationin theformof argumentsfor its position.Thenatureandtypes
of theargumentscanvaryenormously(see[16] [19] [40] for moredetails).However,common
categoriesinclude:threats(failure to acceptthis proposalmeanssomethingnegativewill hap-
pentoyou),rewards(acceptanceof thisproposalmeanssomethingpositivewill happentoyou),
andappeals(you shouldpreferthis optionoverthatalternativefor somereason).Whateverits
preciseform, the role of thesupportingargumentis eitherto modify the recipient’sregionof
acceptabilityor its ratingfunctionoverthis region.In sodoing,argumentshavethepotentialto
increasethe likelihood and/orthe speedof agreementsbeingreached;for example,if agents
preferargumentsthataremorelikely to leadto anagreement(which requiressomemetricon
theagreementspace)it ispossibletoprovethatargumentationleadstoquickeragreement[42]2.
In theformercase,by persuadingagentsto acceptdealsthattheymaypreviouslyhaverejected.
In thelattercase,by convincingagentsto accepttheiropponent’spositiononagivenissue(and
to cease negotiating over it).
3. Game Theoretic Models
Gametheoryis a branchof economicsthatstudiesinteractionsbetweenself-interestedagents.
Like decisiontheory,with whichit sharesmanyconcepts,gametheoryhasits rootsin thework
of vonNeumannandMorgenstern[23]. As its namesuggests,thebasicconceptsof gametheory
arosefrom thestudyof gamessuchaschess.However,it rapidly becameclearthat the tech-
niquesandresultsof gametheorycanequallybeappliedto all interactionsthatoccurbetween
2. Of coursepoorlydesignedargumentationsystemsalsohave thepotentialto increasethelengthof thenegotia-
tion unnecessarily, for exampleif agentskeeprepeatingthesameargumentsad infinitum. However, poordesign
of theotheraspectsof thenegotiationmechanismcanhavesimilarly adverseeffectsandsopotentiallyoverly long
negotiations are not something specific to argumentation-based negotiation.
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self-interestedagents.Gametheoryis relevantto thestudyof automatednegotiationbecause
the participants in such negotiations can reasonably be assumed to be self interested.
Theclassicgametheoreticquestionaskedof anyparticularmulti-agentencounteris: whatis the
best—mostrational—thing anagentcando?In mostmulti-agentencounters,theoverall out-
comewill dependcritically on thechoicesmadeby all agentsin thescenario.This impliesthat
in orderfor anagentto makethechoicethatoptimisesits outcome,it mustreasonstrategically.
That is, it musttakeinto accountthedecisionsthatotheragentsmaymake,andmustassume
thattheywill actsoasto optimisetheir ownoutcome.In negotiation,this means,for example,
takinginto accounttheprivatevaluationsthatagentshaveof thenegotiationissues,theirprivate
deadlinesfor makingadeal,andsoon.Gametheorygivesusawayof formalisingandanalys-
ing such concerns.
Negotiationandbargainingwerestudiedin the gametheory literaturewell beforethe emer-
genceof multi-agentsystemsasa researchdiscipline,andevenbeforethe adventof the first
digital computer.However,computersciencebringstwo importantconsiderationsto thegame
theoretic study of negotiation and bargaining:
1. Gametheoreticstudiesof rationalchoicein multi-agentencounterstypically assume
thatagentsareallowedto selectthebeststrategy from thespaceof all possiblestrate-
gies,by consideringall possibleinteractions.It turnsout thatthesearchspaceof strat-
egies and interactionsthat needsto be consideredhas exponentialgrowth, which
meansthat the problemof finding an optimal strategy is in generalcomputationally
intractable.In computerscience,thestudyof suchproblemsis thedomainof compu-
tationalcomplexity theory[26]. Thereis a significantliteraturedevotedto thedevel-
opmentof efficient (polynomialtime) algorithmsfor apparentlyintractableproblems,
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and the applicationof suchtechniquesto the study of multi-agentencountersis a
fruitful ongoing area of work.
2. Theemergenceof theInternetandWorld-Wide Webhasprovidedanenormouscom-
mercialimperative to the furtherdevelopmentof computationalnegotiationandbar-
gaining techniques [25].
Givenaparticularnegotiationscenariothatwill involveautomatedagents,gametheoretictech-
niques can be applied to two key problems:
1. The designof an appropriateprotocol that will govern the interactionsbetweenthe
negotiation participants. Theprotocoldefinesthe“rulesof encounter”betweenagents
[33]. Formally, a protocolis a setof normsthatconstraintheproposalsthatthenego-
tiation participants are able to make. It is possible to design protocolsso thatany par-
ticular negotiation history has certaindesirableproperties—this is mechanismdesign,
and is discussed in more detail below.
2. Thedesignof a particularstrategy (theagents’decisionmakingmodels)that individ-
ualagentscanusewhile negotiating—anagentwill aim to usea strategy thatmaxim-
ises its own individual welfare. A key difficulty here is that, typically, the strategies
that work bestin theorytendto becomputationallyintractable,andarehenceunusa-
ble by agents in practice.
As notedabove,mechanismdesigninvolvesthedesignof protocolsfor governingmulti-agent
interactions,suchthattheseprotocolshavecertaindesirableproperties.Possiblepropertiesin-
clude, for example [35] p204:
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• Guaranteedsuccess: A protocol guaranteessuccessif it ensuresthat, eventually,
agreement is certain to be reached.
• Maximising social welfare: Intuitively, a protocol maximisessocial welfare if it
ensuresthat any outcomemaximisesthe sum of the utilities of negotiation partici-
pants. If the utility of an outcome for anagent was simply defined in terms of the
amount of money thatagentreceived in theoutcome,thena protocolthatmaximised
social welfare would maximise thetotal amount of money “paid out”.
• Pareto efficiency: A negotiationoutcomeis said to be Paretoefficient if thereis no
other outcome that will make at least one agent betteroff without makingat leastone
other agent worseoff. Intuitively, if anegotiationoutcomeis not Paretoefficient, then
there is another outcome that will make atleastoneagenthappierwhile keepingeve-
ryone else at leastas happy.
• Individual rationality: A protocol is said to be individually rational if following the
protocol— “playing by the rules”—is in thebestinterestsof negotiationparticipants.
Individually rationalprotocolsareessentialbecausewithout them,thereis no incen-
tive for agents to engage in negotiations.
• Stability: A protocolis stableif it providesall agentswith anincentive to behave in a
particular way. The best-known kind of stability is Nashequilibrium: two strategiess
ands' are said to be in Nash equilibrium if under theassumptionthat one agent is
usings , the other can do nobetter than uses' , and vice versa.
• Simplicity: A “simple” protocolis onethatmakestheappropriatestrategy for a nego-
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tiation participant “obvious”. Thatis, a protocolis simpleif usingit, a participantcan
easily (tractably) determine the optimal strategy.
• Distribution: A protocolshouldideally be designedto ensurethat thereis no single
point of failure (such as a single arbitrator),andideally, so asto minimisecommuni-
cation between agents.
Thefactthatevenquitesimplenegotiationprotocolscanbeprovento havesuchdesirableprop-
ertiesastheseaccountsin no smallpartfor thesuccessof gametheoretictechniquesfor nego-
tiation [17]. As anexample,considerthemonotonicconcessionprotocolwith Zeuthenstrategy
[33] pp40-49.Themonotonicconcessionprotocolfor two negotiationparticipantsis asfollows.
Negotiationproceedsin asequenceof rounds,whereateveryround,eachagentputsforwarda
proposal.If theproposals“overlap”, thenagreementhasbeenreached.If theproposalsdo not
overlap,thennegotiationproceedsto afurtherround,wheretheagentseithermakea concession
orelseputforwardtheproposaltheymadeontheprecedinground.If neitheragentmakesacon-
cession,thennegotiationterminateswith a“conflict deal”.Thissimpleprotocolensuresthatne-
gotiation either monotonicallyproceedstowardsa solution, or else terminates.Now, what
strategyshouldanagentusewhenfacedwith suchaprotocol?Onepossibilityis to usetheZeu-
then strategy. This strategy essentially says that:
• the agentthat shouldconcedeis the onewith the mostto lose from the negotiation
breaking down;
• theconcessionthatshouldbemadeis theminimumrequiredto changethebalanceof
risk—so that the other agent is required to concede on subsequent rounds.
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Bothof thesepropertiescanbeformalisedquiteeasily[33] p43.It canbeprovedthatusingthe
Zeuthenstrategywhenplayingthemonotonicconcessionprotocolmeansagentswill cometo
reachagreementon a dealthat is Paretooptimal.Unfortunately,theZeuthenstrategyis not in
equilibrium; thereis an incentiveto deviatefrom thestrategyat the lastnegotiationstep[33]
p48.Moreover,the strategyis computationallycomplex,requiringan exponentialnumberof
calculationsof theagent’sutility functionateachnegotiationroundin orderto computetheop-
timal deal.Nevertheless,it is striking thatsuchasimpleandintuitive protocolcanbeprovento
have desirable properties.
Despitethesevery obviousadvantages,however,therearea numberof problemsassociated
with the use of game theory when applied to automated negotiation:
• Gametheoryassumesthat it is possibleto characterisean agent’s preferenceswith
respect to possible outcomes.Humans, however, find it extremelyhardto consistently
define their preferences over outcomes. In general, humanpreferences cannot be
characterised even by a simple orderingover outcomes,let aloneby numericutilities
[32] p475-480. In scenarios wherepreferencesareobvious(suchasthecaseof a per-
son buying aparticularCD andattemptingto minimisecosts),gametheoretictech-
niques may work well. With more complex (multi-issue) preferences, it is much
harder to use them.
• Thetheoryhasfailed to generatea general modelgoverningrationalchoicein inter-
dependentsituations[46]. Instead,the discipline hasproduceda numberof highly
specialisedmodelsthat are applicableto specific typesof interdependentdecision
making(e.g.thevon Neumann-Morgensternsolutionto two-persongames[23]). As
Binmore notes, in non-cooperative (a sub-branch of game theory) theories:
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...conclusions(of non-cooperative models) only apply to one specific
game. If the details of the rules are changedslightly, the conclusions
reached need no longer be valid [5] p. 196.
• Gametheorymodelsoftenassumeperfectcomputationalrationalitymeaningthatno
computationis requiredto find mutuallyacceptablesolutionswithin a feasiblerange
of outcomes.Furthermore,this spaceof possibledealsis often assumedto be fully
known by theagents,asis thepotentialoutcomevalues.Thisassumptionis rarelytrue
in mostrealworld cases;agentstypically know their own informationspace,but they
do not know thatof their opponent.However, evenif thejoint spaceis known, know-
ing thata solutionexistsis entirelydifferentto knowing whatthesolutionactuallyis.
Chessis aclassicexampleof thispoint.Thegamehasasolution—astrategy for white
or blackwhich is eithera win or a draw, but thesearchis computationallycomplex.
Therefore,the notion of perfectrationality, althoughuseful in designing,predicting
andproving propertiesof a system,is not altogetherusefulin practice.Firstly, it can-
not actuallybe attained:physical mechanismstake time to processinformationand
selectactions,hencethebehaviour of realagentscannotimmediatelyreflectchanges
in theenvironmentandwill generallybesub-optimal[39]. Secondly, it doesnot pro-
vide a meansof analysingthe internal designof an agent;one rational agentis as
good as another.
Despitetheseproblems,gametheoryis extremelycompellingasa tool for automatednegotia-
tion. In caseswhereit is possibleto characterisethepreferencesandpossiblestrategiesof ne-
gotiation participants, then game theory has much to offer.
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3. Heuristic Approaches
Themajormeansof overcomingtheaforementionedlimitationsof gametheoreticmodelsis to
useheuristicmethods.Suchmethodsacknowledgethatthereis a costassociatewith computa-
tion anddecisionmakingandsoseekto searchthenegotiationspacein anon-exhaustivefash-
ion. This has the effect that heuristic methodsaim to producegood, rather than optimal
solutions.Themethodsthemselvesmayeitherbecomputationalapproximationsof gametheo-
retictechniquesor theymaybecomputationalrealisationsof moreinformalnegotiationmodels
(e.g.[29], [30]). Examplesof suchmodelsinclude:[3], [8], [18], [36], [41]. Thekeyadvantages
of the heuristic approach can be stated as follows:
• the modelsare basedon realistic assumptions;hencethey provide a more suitable
basisfor automationandthey can,therefore,beusedin a wider varietyof application
domains;
• thedesignersof agents,who arenot weddedto gametheory, canusealternative, and
less constrained, models of rationality to developdifferent agent architectures.
Thecentralconcernof this line of work is to modeltheagent’sdecisionmakingheuristically
duringthecourseof thenegotiation(generallyspeaking,thechosenprotocoldoesnotprescribe
anoptimalcourseof action).To delvedeeperinto thisareawewill concentrateontheheuristic
modelwehavedevised;wedevelopedasetof deliberationmechanismsthatwork within afair-
ly free negotiation protocol3 [8][9][10] [37].
The spaceof possibleagreementsis quantitativelyrepresentedby contractshavingdifferent
valuesfor eachissue.Eachagentthenratesthesepointsin thespaceof possibleoutcomesac-
cordingto somepreferencestructure,capturedby autility function.Proposalsandcounter-pro-
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19
posalsare then offers over single points in this spaceof possibleoutcomes,and search
terminateseitherwhenthetime to reachanagreementhasbeenexceededor whena mutually
acceptablesolution,a point of intersectionof the agents’acceptableoutcomessets,hasbeen
reached.
An agentarchitecturethatmodelsthedecisionsinvolvedin thesearchfor mutuallyacceptable
solutionshasalsobeendeveloped[9]. Whereastheprotocolnormativelydescribestheorder-
ingsof actions,thedecisionmakingmechanismsdescribethepossiblesetof agentstrategiesin
usingtheprotocol.Thesestrategiesarecapturedby anegotiationarchitecturethatis composed
of responsiveanddeliberativedecisionmechanisms.Decisionmakingwith theformermecha-
nismis basedon a linearcombinationof simplefunctionscalledtactics, which manipulatethe
utility of contracts[8]. Thelattermechanismsaresubdividedinto trade-offandissuemanipu-
lation mechanisms[9]. The formergeneratesoffers thatmanipulatethevalue,ratherthanthe
overallutility, of theoffer.Therationalefor thetrade-offmechanism,like persuasiveargumen-
tation, is to makeproposalsthat aremoreattractiveto the opponent.This is achievednot by
“providing additionalmeta-levelinformation” (seesection4), but by providingcontractsthat
are“closer” to theopponent’slastoffer. The issuemanipulationmechanismaimsto increase
thelikelihoodof anagreementby addingandremovingissuesinto thenegotiationset.Theissue
3. The negotiation protocol doesnot prescribean agent’s behaviour, but it doesconstrainits action selection
problemsolvingthroughtheuseof normative rulesof interaction.Theserulestemporallyorder, accordingto the
agent’s roles,communicationutterancesby specifyingbothwho cansaywhat,aswell aswhen.Specifically, the
protocol is a repeated,sequentialmodelwhereoffers areiteratively exchanged.Underthis protocol,agentsare
fully committedto theirutterancesandutterancesareprivate(unlike,say, thefirst-priceopen-cryEnglishauction,
whereall offersarepublicly “heard”by theotherinteractionparticipants).Theprotocolis distributed,symmetric,
supportsbi and/ormulti-agentnegotiation as well as distributive and integrative negotiation, involving one or
many issuesrespectively. Theutterances(proposalsor counter-proposals)arebasedon previouscommentsmade
by otheragents,andrepresenta singlecompleteproposalfor a solution.Thereareno critiquesandcounter-pro-
posals are based on the object of negotiation (which we term a contract).
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20
manipulationmechanismdynamicallyaltersthestructureof thenegotiationobject,helpingto
escapelocalminimain thenegotiationdynamics.It doesthiseitherby increasingthesetof pos-
sibleoutcomes(adding),whennegotiationis in deadlock,or, alternatively,removing“noisy”
issuesthatareobstructingthenegotiationprogress.Sinceagentshaveto mutuallyagreeon the
setof issuesinvolved in negotiation,the issuemanipulationdialoguecanbe interpretedasa
mechanismthatmodifiesthedimensionalityof thesolutionspace.Theothermechanisms,re-
sponsiveandtrade-off,canthensearchthealteredsolutionspace.Whentakentogether,these
threemechanismsrepresentacontinuumof possibledecisionmakingcapabilities:rangingfrom
behavioursthatexhibitgreaterawarenessof environmentalresourcesandlessto solutionqual-
ity, to behavioursthatattemptto acquireagivensolutionquality independentlyof theresource
consumption.
Generallyspeaking,while heuristicmethodsdo indeedcircumventsomeof theshortcomings
of game theoretic models, they also have a number of comparative disadvantages:
• the modelsoften selectoutcomes(deals)that are sub-optimal;this is becausethey
adoptan approximatenotion of rationality andbecausethey do not examinethe full
space of possible outcomes;
• the modelsneedextensive evaluation, typically throughsimulationsand empirical
analysis,sinceit is usually impossibleto predict preciselyhow the systemand the
constituent agents will behave in a wide variety of circumstances.
4. Argumentation-Based Approaches
All of the techniqueswe havediscussedsofar havebeencentredon the tradingof proposals.
Although,astheprevioussectionsdemonstrate,this canbedonein a very sophisticatedway,
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21
the various approaches have three main limitations:
• The proposalsthemselvesgenerallydenotesinglepoints in the spaceof negotiation
agreements (a single X or O in Figure 1)4;
• Theonly feedbackthatcanbemadeto aproposalis acounter-proposal,which itself is
another point in the space, or an acceptance or withdrawal;
• It is hardto changethesetof issuesundernegotiationin thecourseof a negotiation
(which correspondsto changingthe negotiation spaceof Figure 1 by addingnew
dimensions).
Theaim of argumentation-basednegotiationis to removetheselimitations.Thebasicideabe-
hindtheargumentation-basedapproachis toallowadditionalinformationtobeexchanged,over
andaboveproposals.This informationcanbeof a numberof different forms,all of which are
argumentswhichexplainexplicitly theopinionof theagentmakingtheargument.Thus,in ad-
dition to rejectingaproposal,anagentcanoffer acritiqueof theproposal,explainingwhy it is
unacceptable.This hastheeffectof identifyinganentireareaof thenegotiationspaceasbeing
not worth exploringby theotheragent.Similarly, anagentcanaccompanya proposalwith an
argumentwhich sayswhy theotheragentshouldacceptit. This latterkind of argumentmakes
it possibleto changetheotheragent’sregionof acceptability(by alteringits preferences),and
alsoprovidesameansof changingthenegotiationspaceitself—without theability to arguefor
theworthof anewelementin thenegotiationobject,thereceivingagentwouldnot, in general,
haveanybasisonwhichto determineits value.Thiskind of persuasiveargumentationdoesnot
4. Though,of course,agentsreceiving proposalsmay assumeall kinds of implicit informationon the basisof
them.
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22
haveto betieddirectly to proposalseither.Forexample,in humanargumentation,it is possible
to makethreatsor offer rewards,andthesekindsof argumentcanbecapturedin this approach
[19]. As in humanargumentation,agentsmaynot betruthful in theargumentsthattheygener-
ate.Thuswhenevaluatinganargument,therecipientneedsto assesstheargumenton its own
meritsandthenmodify thisby its ownperceptionof theargument’sdegreeof credibility in or-
der to work out how to respond.
Again to providemoredetailsof this broadclassof negotiation,we focuson modelswe have
developed.To thisend,thewayin whichargumentationfits into thegeneralnegotiationprocess
wasdefinedin [38] wherea simplenegotiationprotocolfor tradingproposalswasaugmented
with a seriesof illocutionarymoveswhich allow for thepassingof arguments.It is possibleto
think of thepassingof anargumentusingoneof thesemovesasmarkinga transitionfrom the
negotiationprotocolto a separateargumentationprotocolwhich definestherulesof thegame
for carryingoutanargumentdialogue(possibleprotocolsfor suchdialogueshavebeensuggest-
edin [1], [2]). Whentheargumentdialogueterminates,theagentsmakethereversetransition
and pick up the negotiation dialogue once again.
Theexactargumentationmechanismwe employis logic-based[27] andbuildson work in ar-
gumentationasanapproachto handlingdefeasiblereasoning.Thismakesit possiblefor agents
to handlingcontradictorystatements(which frequentlyoccurduring arguments)without col-
lapsinginto triviality, andallow conflicting argumentsto beresolved.Usingargumentationin
real agents(asopposedto simplecollectionsof logical statements)meanshandlingthe com-
plexitiesof theagents’mentalattitudes,communicationbetweenagents,andtheintegrationof
the argumentation mechanisms into a complex agent architecture.
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23
Theseissueswerediscussedin [28], whereweshowedhowto augmentastandardmodelof ar-
gumentationto work for agentswhichreasonusingbeliefs,desiresandintentions.Wealsodis-
cussedhow to makeuseof multi-contextsystems[12], originally proposedas a meansof
providingefficient theoremproversfor modallogics,to integrateargumentationinto a belief-
desire-intentionagentarchitecture.Thislatterstrandof work wasfurtherdevelopedin [34], and
thishasledto animplementationin whichagentsnegotiateusingargumentationin orderto con-
struct joint plans.
Forthefuture,two mainareasof work remain.Thefirst is in thedefinitionof suitableargumen-
tationprotocols,thatis, setsof rulesthatspecifyhowagentsgenerateandrespondto arguments
baseduponwhattheyknow.Initial attemptsatdefiningsuchprotocolsaregivenin [1], [2], but
asdiscussedthere,it seemsthatwhendefininganargumentationprotocol,we “hard-wire” in
theattitudethata givenagenttakeswhennegotiatingwith others,defining,for instance,when
anargumentis foundto bepersuasive,andwhenits groundscanbequestioned.As aresult,we
mayendup with negotiatorswhich arepossiblyratherinflexible in their argumentationstance
(thoughmoreflexible thannegotiatorswhich cannotargue).Sincethis seemsratherlimiting,
we needto investigatethis areamorewith theaim of discoveringmoreflexible argumentation
protocolsthanwecurrentlyhave.Thesecondmainareaof work is alsorelatedto argumentation
protocols,andspecificallythe transitionbetweenthe underlyingnegotiationprotocolandthe
argumentationprotocol.Whenis theright time to makethis transition,whenis it right to start
anargument?Clearlyit only makessenseto engagein thecomplexbusinessof argumentation
whenit will helpthenegotiation,but we needto translatethis high-levelnotionof “rightness”
into some more concrete decision criterion that can be built into our agents.
While theseissuesstill needto beaddressedin orderto build fully functionalagentscapableof
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24
argumentation-basednegotiation,thework describedin thissectionhaslaid thefoundationsfor
building flexible negotiators.Suchagentswill havetheability to bepersuasiveandsoachieve
agreementswhich non-argumentationbasednegotiatorscannot.However,the problemwith
suchmethodsis thattheyaddconsiderableoverheadsto thenegotiationprocess,not leastin the
constructionandevaluationof arguments.As a result,we imaginethatagentswhichcanargue
in supportof their negotiationswill only everrepresenta small,thoughimportant,classof au-
tomated negotiators.
5. Conclusions
This paperhasarguedthatautomatednegotiationis a centralconcernfor multi-agentsystems
research.To thisend,agenericframeworkfor classifyingandviewingautomatednegotiations
hasbeendeveloped.Thisframeworkwasthenusedto discussandanalysethethreemainmeth-
odsof approachthathavebeenadoptedto automatednegotiation;namely,gametheoretic,heu-
ristic andargumentation-basedapproaches.For eachapproach,a brief appraisalof its relative
meritsanddrawbacksis presented.This assessmentwasgenerallyperformedin thecontextof
the authors’ own models.
It is clearthatmuchresearchstill needsto beperformedin theareaof automatednegotiation.
This researchobviouslyincludesextendinganddevelopingthespecificapproachesthathave
beendiscussedhereinandevendevelopingnewmethods(suchasthosebasedon particledy-
namics[17], for example).However,therearealsoanumberof broaderissues,which, to date,
havereceivedcomparativelylittle attention.Theseincludethefollowing. Firstly, thedevelop-
mentof a bestpracticerepositoryfor negotiationtechniques.That is, a coherentresourcethat
describeswhich negotiationtechniquesarebestsuitedto a given type of problemor domain
(muchlike theway thatdesignpatternsfunction in object-orientedanalysisanddesign[11]).
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25
Foreachentry,therelativestrengthsandweaknessesneedto beenumerated,theunderpinning
assumptionsneedto be explicitly stated,andthe likely operationalcharacteristicsneedto be
listed.At present,muchof this knowledgeis implicit anddeveloperstendto simply adoptthe
technique(or family of techniques)with which they are most familiar. Secondly,work on
knowledgeelicitation and acquisitionfor negotiationbehaviourneedsto be advanced.At
present,thereis virtually no work on how a usercaninstructanagentto negotiateon their be-
half.Suchinstructionneedsto conveythebroadnegotiationattitudethattheagentshouldadopt,
theextentto which theagentcannegotiateautonomously,andthedegreesof freedomthatthe
agentcanexploreduringanegotiationepisode.Finally, andrelatedto theprevioustwo points,
work onproducingpredictablenegotiationbehaviourneedsto bedeveloped.Thiswork is need-
edto ensurethatusersarecomfortableto delegatenegotiationdecisionsto anautonomouspiece
of softwareandthatwhentheydo sotheyaresurethattheagentwill actwithin its negotiation
mandate.
Acknowledgements
This work hasbeenpartially supportedby theEPSRCunderthegrantGR/M07076andby the
EU under grant IST-1999-10948.
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