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A Framework for Argumentation-Based Negotiation

TL;DR: A general framework for negotiation in which agents exchange proposals backed by arguments which summarise the reasons why the proposals should be accepted is described.
Abstract: Many autonomous agents operate in domains in which the cooperation of their fellow agents cannot be guaranteed. In such domains negotiation is essential to persuade others of the value of co-operation. This paper describes a general framework for negotiation in which agents exchange proposals backed by arguments which summarise the reasons why the proposals should be accepted. The argumentation is persuasive because the exchanges are able to alter the mental state of the agents involved. The framework is inspired by our work in the domain of business process management and is explained using examples from that domain.

Summary (3 min read)

1 Introduction

  • In such environments, agents often have no inherent control over one another and so the only way they can influence one another’s behaviour is by persuasion.
  • In other cases, the persuadee may be unwilling to accept the proposal initially and must be persuaded to change its beliefs, goals or preferences so that the proposal, or some variant thereof, is accepted.
  • On leave from Laboratorio Nacional de Informática Avanzada—LANIA.
  • The authors outline the components of a formal model for the process of argumentation-based negotiation which can ultimately be used to build negotiating agents for real world applications.
  • Finally, the authors indicate how these arguments can be generated and interpreted by agents.

2 Argumentation in Business Process Management

  • This section describes the scenario which will be used to illustrate the principles and concepts of their model of argumentation.
  • The scenario is motivated by work in the ADEPT project [8] which has developed negotiating agents for business process management applications.
  • In the case of bespoke services the process is more complex.
  • If such a survey is warranted, the DD agent negotiates with the SD agent for the Survey Customer Site service.
  • On completion of the network design and costing, the DD agent informs the CSD agent which informs the customer of the service quote.

3 Negotiation model

  • The authors model describes the process of a single encounter negotiation between multiple agents over a deal.
  • Deals are always between two agents, though an agent may be engaged simultaneously in negotiation with many agents for a given deal.
  • The deliberation capability of the participating agents—in the form of an internal state in which the agent may register the history of the negotiation as well as the evolution of its own theoretical elements on which its decisions are founded.
  • The minimal shared meaning of the acceptable illocutions—this is captured in the way that a received illocution should be interpreted when heard by an agent, and by making explicit the conditions that enable an agent to use (or ‘generate’) a given illocution at a given time.
  • A minimal set of concepts which are necessary to represent the static components in automated negotiation are presented in Section 3.1, and the dynamic components—the concepts of a negotiation thread and a negotiation state—are introduced in Section 3.2.

3.1 A Basic Negotiation Ontology

  • Negotiation requires communication between the agents and, for it to be unambiguous, each agent must have a unique identifier.
  • (Note this constant does not mean “don’t care”.).
  • In this work the authors adopt the simplest solution and assume a common language.
  • The negotiation dialogue between two agents consists of a sequence of offers and counter offers containing values for the issues.
  • This is followed by an exchange of possibly many counter proposals (that agents may reject) and many persuasive illocutions.

3.2 Negotiating agents

  • The Dialogical Framework described in the previous section represents the static components of the negotiation model—those that are fixed for all negotiations.
  • In order to capture essential aspects of persuasion it is necessary to assume that the agents have memory and are deliberative.
  • In an extension to their previous work [16], the authors want to capture the idea that new issues may arise during the negotiation process.
  • As an illustration of how these notions are used, consider the following example: Example 1.
  • The CSD agent is negotiating with a V Ci agent for the Vet Customer service for company A.

3.3 Persuasive agents

  • The other persuasive illocutionary acts, threaten a b not not t and reward a b not not t with CL, can contain arguments as long as and/or are appeals, or, recursively, contain appeals.
  • In their domain, and in other work on MAS [2], the social role between the agents is a determining factor in deciding which argument should be preferred.
  • Precisely which social roles correspond to a power relation between the agents depends on the particular domain.
  • Given the two argument pairs Arg and Arg such that Attacks Arg Arg then Arg will be preferred to Arg , which the authors write as Arg Arg , if and only if Support Arg Support Arg .
  • DD indicates that it must have the service completed within 24 hours.

3.4 Interpretation and Generation of Illocutions

  • For pragmatic reasons, the authors separate the definition of the semantics of illocutions into two different operations, I and G (see examples 3 and 4).
  • The underlying idea is that any illocution may introduce new issues into a negotiation, while appeals may, in addition, modify the preference relationships and the agent’s theory.
  • Complete illocutionaryhistories allow agents with total recall to be modelled.
  • The authors do not update agents’ theories in this minimal semantics because they wish to keep the interpretation of illocutions reasonably neutral with respect to the agents’ internal architectures.
  • The following example illustrates a simple negotiation dialogue between two agents and contains a fragment of a G function.

5 Conclusion

  • This paper has introduced a novel framework for describing persuasive negotiations between autonomous agents.
  • The framework has been strongly influenced by their experience of business process management applications and this makes us confident that it can capture the needs of other real world applications.
  • The authors realise that there are a number of issues which require further investigation.
  • Finally, the authors make the simplifying assumption that negotiating agents have a common notion of deduction.
  • This may be inadequate for some domains, in which case it will be necessary for agents to be able to discuss what rules of inference are appropriate.

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A framework for argumentation-based negotiation
Carles Sierra
z
?
, Nick R. Jennings
z
,PabloNoriega
y
??
, Simon Parsons
z
z
Department of Electronic Engineering,
Queen Mary and Westeld College,
University of London, London E1 4NS, UK.
f
C.A.Sierra, N.R.Jennings, S.D.Parsons
g
@qmw.ac.uk
y
Articial Intelligence Research Institute, IIIA.
Spanish Scientic Research Council, CSIC.
Campus UAB, 08193 Bellaterra, Barcelona, Spain.
f
sierra, pablo
g
@iiia.csic.es
Abstract. Many autonomous agents operate in domains in which the co-
operation of their fellow agents cannot be guaranteed. In such domains negoti-
ation is essential to persuade others of the value of co-operation. This paper de-
scribes a general framework for negotiation in which agents exchange proposals
backed by arguments which summarise the reasons why the proposals should be
accepted. The argumentation is persuasive because the exchanges are able to alter
the mental state of the agents involved. The framework is inspired by our work
in the domain of business process management and is explained using examples
from that domain.
Keywords: Automated negotiation, Argumentation, Persuasion.
1 Introduction
Negotiation is a key form of interaction in systems composed of multiple autonomous
agents. In such environments, agents often have no inherent control over one another
and so the only way they can inuence one another’s behaviour is by persuasion. In
some cases, the persuadee may require little or no convincing to act in the way desired
by the persuader , for example because the proposed course of action is consistent wit h
their plans. However, in other cases, the persuadee may be unwilling to accept the pro-
posal initially and must be persuaded to change its beliefs, goals or preferences so that
the proposal, or some variant thereof, i s accepted. In either case, the minimum require-
ment for negotiation is for the agents to be able to make proposals to one another. These
proposals can t hen either be accepted or rejected as is the case in the contract net pro-
tocol [17], for instance. Another level of sophistication occurs when recipients do not
just have the choice of accepting or rejecting proposals, but have the option of making
?
On sabbatical leave from IIIA
y
thanks to a Spanish MEC grant PR95-313. Research partially
supported by the Spanish CICYT project SMASH, TIC96-1038-C04001.
??
On leave from Laboratorio Nacional de Inform´atica AvanzadaLANIA. R´ebsamen, 80;
Xalapa, Veracruz, Mexico. Enjoying a Mexican CONACYT grant [69068-7245].

counter offers t o alter aspects of the proposal which are unsatisfactory [16]. An even
more elaborate form of negotiation—argumentation-based—is that in which parties are
able to send justications or arguments along with (counter) proposals indicating why
they should be accepted [11, 13, 18]. Arguments such as: “this is my nal offer, take
it or leave i t ”, “last ti me this job cost $5, I’m not going to pay $10 now”, and “the job
will t ake l onger than usual because one of the workers is off sick” may be necessary to
change the persuadee’s goals or preferences.
This paper deals with argumentation-based negotiation. Because this is a large re-
search topi c [9, 19] we limit our scope to argumentation between computational agents
where a persuader t ries to convince a persuadee to undertake a particular probl em solv-
ing t ask (service) on its behalf. We outline t he components of a formal model for the
process of argumentation-based negotiation which can ultimately be used to build ne-
gotiating agents for real world applications. While we draw on our previous work i n this
area, in thi s paper we shift our attention from the mechanisms for generating counter
proposals [16] and t hose for generating and interpreting arguments [13] to the social
aspects of the negotiation. Moreover, we take advantage of the work on Dialogical
Frameworks introduced in [12] to dene the static aspects of the negotiation process:
shared ontology, social relations, communication l anguage and protocol. We dene a
minimal not i on of the state of an agent which captures the evolutionary character of
negotiation—enabling t he resulting model to recognise different types of arguments
that agents can make in support of t heir proposals. Finally, we indi cate how t hese argu-
ments can be generated and interpreted by agents.
In the paper we discuss three types of illocutions: (i) threats—failure to accept this
proposal means something negative will happen to the agent; (ii) rewards—acceptance
of this proposal means something positive will happen to the agent; and (iii) appeals
the agent should prefer t his option over t hat alternative for this reason. We realise these
are a subset of the illocutions that are involved in persuasive negotiation (see [9] for a
list based on psychological research), but our emphasis is in providing an overarching
framework in which the key components of argumentation can be described, rather t han
providing an exhaustive formalisation of all the argument types which can be found in
the literature. We illustratethese constructs through a running example introduced in the
following section. The main contribution of this work i s, therefore, to provide a formal
framework in which agents can undertake persuasive negotiation to change each other’s
beliefs and preferences using an expressive communication language. Moreover, the
framework is neutral with respect to the agent’s internal architecture and imposes few
constraints on it s formal resources.
2 Argumentation in Business Process Management
This section describes the scenario which will be used to illustrate the principles and
concepts of our model of argumentation. The scenario is motivated by work in the
ADEPT project [8] which has developed negotiating agents for business process man-
agement applications. In particular, we consider a multi-agent system for managing a
British Telecom (BT) business process—namely, providing a quotation for designing
a network which offers particular services to a customer (Figure 1). The overall pro-

cess receives a customer service request as its input and generates as its output a quote
specifying how much it would cost to build a network to realise that service. Here
we consider a subset of t he agents involved in this activity: the customer service divi-
sion (CSD) agent, t he design division (DD) agent, t he surveyor department (SD) agent,
and the various agents who provide the out-sourced service of vetting customers (VC
agents). A full account of all the agents and their negotiations is given in [16].
Provide_
Customer_
Quote
Cost_&_Design_Customer_Network
Survey_
Customer_Site
Vet_
Customer
Customer
Service
Division Agent
(CSD)
Design
Department
Agent
(DD)
Surveyor
Departmen
t
Agent
(SD)
Customer
Vet
Customer
Agents
(VC)
Fig. 1. Agent system for BT’s
P r ovide C ustomer Quote
business process. The direction of
the arrow indicates who provides the service labelling the arrow to whom.
The rst stages of t he Provide Customer Quote service involve the CSD agent cap-
turing basic i nformation about the customer and vetting the customer in terms of their
credit worthiness. The latter service i s performed by one of the VC agents and ne-
gotiation is used to determine which one is selected. If the customer fails the vetting
procedure, then the quot e process terminates. Assuming the customer is satisfactory,
the C SD agent maps their requirements against a service portfolio. If the requirements
can be met by a standard off-the-shelf portfolio i t em then an immediate quote can be
offered based on previous examples. In the case of bespoke services t he process is more
complex. The CSD agent negotiates with the DD agent for the service of costing and de-
signing the desired network service. To prepare a network design it is usually necessary
to have a detailed plan of t he existing equipment at the customer’s premises. Sometimes
such plans might not exist and sometimes they may be out of date. In either case, the
DD agent determines whether t he customer site(s) should be surveyed. If such a survey
is warranted, the DD agent negotiates with the SD agent for the Survey
Customer Site
service. This negotiation differs from the others present in this scenario in that the two
agents are part of the same department. Moreover, the DD agent has a degree of author-
ity over SD. Agent negotiation is still required to set the timings of the service, but the
SD agent cannot simply refuse to perform the service. On completion of the network
design and costing, the DD agent informs the CSD agent which i nforms t he customer
of the service quote. The business process t hen terminates.
The precise nature of the argumentation which can occur in the aforementioned ne-
gotiations is determined by three main factors: (i) the negotiation arity—pairwise (1
to 1) negotiations (e.g. the CSD and DD agents for t he design network service) dif-
fer from 1 to many negotiations (e.g. the CSD and VC agents for the Vet
Customer

Type Id Parties Content Comments
Threaten 1 CSD-VCs
Match the offer I have from another VC, otherwise I’ll
break off this negotiation.
Threaten to terminate current nego-
tiation thread.
2 CSD-VCs
Make sure you get back to me in the specied time period
or I won’t involve you in future rounds of bidding.
Threaten to terminate all future ne-
gotiation threads.
3 DD-SD
If you cannot complete the service sooner, I’ll inform your
boss th at we missed the d eadline because of you.
Threaten to inform outside party of
(perceived) poor performance.
Reward 4 CSD-DD
If you produce this design by this time we’ll be able to get
the quote to our major customer ahead of time.
Indicate positive effect of perform-
ing action by specied time.
5 CSD-VCs
If you vet this customer by this time, I’ll make sure you’re
involved in subsequent rounds of bidding.
Promise future involvement for ac-
cepting current proposal.
Appeal 6 CSD-VCs
Last time you vetted this customer, it took this length of
time and cost this much.
Appeal to precedent.
7 CSD-DD
You must complete this design within 48 hours because
company policy says customers must be responded to
within this time frame.
Appeal to (company’s) prevailing
practice.
8 VC-CSD
This customer may b e in nancial trouble, therefore more
time is needed to carry out a higher quality vetting.
Appeal to (CSD’s) self interest.
9 DD-CSD
The design will take longer than normal because one of o ur
surveyors is on holiday this week.
Revealing new information.
10 SD-DD
Customer has m any premises and they all need to be sur-
veyed, thus this service will take longer than normal.
Revealing new information.
Fig. 2. Sample arguments in the BT application.
service); (ii) the power relations [2] between the negotiators—most negotiations are
peer-to-peer, but t he DD and SD negotiation over the Survey
Customer Site service is
an example of boss-to-subordinate negotiation; and (iii) the organisational relationship
of the negotiators—some negotiations are between agents of the same organisation (e.g.
the CSD, DD and SD agents), while others are between agents of different organisations
(e.g. the CSD and VC agents). Our experience in the domain shows that the argumen-
tation between agents can be captured by the three types of argument mentioned in
the Int roduction—t hreats, rewards and appeals. Some examples of such arguments are
given in Figure 2.
3 Negotiation model
Our model describes the process of a single encounter negotiation between multiple
agents over a deal. Deals are always between two agents, though an agent may be en-
gaged simultaneously in negotiation with many agents for a given deal. Negotiation
is achieved through the exchange of illocutions in a shared communication l anguage
CL
. The actual exchange of illocutions is driven by the participating agents individual
needs and goals—something that will not be part of this negotiation model. Neverthe-
less, this exchange is subject to some minimal shared conventions on the int ended usage
of the illocutions in
CL
, and a simple negotiation protocol. These conventions relate to:
1. The elements that are relevant for t he negotiation of a deal—in the form of issues
and values that may evolve as negotiation proceeds.

2. The rationality of the participating agents—in terms of some form of preference
relationships or utility functions which enable the agents to evaluate and compare
different proposals.
3. The deliberation capability of the participating agents—in the form of an internal
state in which the agent may register the history of the negotiation as well as the
evolution of i t s own theoretical elements on which it s decisions are founded.
4. The minimal shared meaning of the acceptable illocutions—this is captured in the
way that a r eceived illocution should be interpreted when heard by an agent, and
by making explicit the conditions t hat enable an agent to use (or ‘generate’) a given
illocution at a given time.
A minimal set of concepts which are necessary to represent the static components in
automated negotiation are presented i n Section 3.1, and the dynamic components—the
concepts of a negotiation thread and a negotiation state—are introduced in Section 3.2.
Social aspects that are relev ant for persuasive arguments are dealt with in Section 3.3,
and the process of interpreting and generating illocutions is illustrated in Section 3.4.
3.1 A Basic Negotiation Ontology
Negotiation requires communication between the agents and, for it to be unambiguous,
each agent must ha v e a unique identier. We denote t he set of identiers of the agents in-
volved in a negotiation as
Agents
3
. The agents involved in a negotiation will have a va-
riety of social relationships with one another. These relationships have an important im-
pact upon t he persuasion and argumentation process. For instance, prestigious speakers
have a large persuasive impact and peers can be persuaded more easily than non-peers
[9]. To model this characteristic, we assume that a general and shared social relation
is dened between the agents. This relation can be modelled as a binary function over
a set of social roles, denoted as
Roles
. In the BT scenario, for example,
Roles
would
be:
f
C ustomer C ontr actor B oss P eer
g
. Finally, we assume that agents, when ne-
gotiating, interchange illocutions in a common communication language
CL
dened
over a set of illocutionary particles whose propositional content is expressed in a shared
logical l anguage
L
4
. The precise nature of
L
is unimportant in our model (e.g. it could
be a propositional language or a modal l anguage), however it must contain at least the
following:
1. Variables. To represent t he issues under negotiation. They have to be variables be-
cause issues need to be bound to different values during negotiation.
2. Constants. To represent values for the issues under negotiation. A special constant
‘?’ is needed to represent the absence of value, and allow for underdened proposals
between agents. (Note this constant does not mean “don’t care.)
3
In practice, this set may change dynamically (e.g. new vetting companies may be created and
old ones may disappear). However, since this process can be seen as independent from the
negotiation process, our model is presented with respect to a xed set.
4
In practice, agents often have heterogeneous information models and so need to use one of the
variety of techniques for allowing them to interoperate [5, 7]. However, in this work we adopt
the simplest solution and assume a common language.

Citations
More filters
01 Jan 1991

326 citations

Journal ArticleDOI
TL;DR: A logic-based formalism for modeling of dialogues between intelligent and autonomous software agents, which enables representation of complex dialogues as sequences of moves in a combination of dialogue games, and allows dialogues to be embedded inside one another.
Abstract: We present a logic-based formalism for modeling of dialogues between intelligent and autonomous software agents, building on a theory of abstract dialogue games which we present. The formalism enables representation of complex dialogues as sequences of moves in a combination of dialogue games, and allows dialogues to be embedded inside one another. The formalism is computational and its modular nature enables different types of dialogues to be represented.

285 citations

Proceedings ArticleDOI
14 Jul 2003
TL;DR: The proposed argumentation framework is dynamic, with arguments and their strength depending on the particular context that the agent finds himself, thus allowing the agent to adapt his decisions in a changing environment.
Abstract: This paper presents an argumentation based framework to support the decision making of an agent within a modular architecture for agents. The proposed argumentation framework is dynamic, with arguments and their strength depending on the particular context that the agent finds himself, thus allowing the agent to adapt his decisions in a changing environment. In addition, in order to enable the agent to operate within an open environment where the available information may be incomplete we have integrated abduction within this argumentation framework. This is particular useful when the agent finds himself in a dilemma and hence needs additional information to resolve this. We have also developed, motivated by work in Cognitive Psychology, within the same framework an argumentation based personality theory for agents thus incorporating a dimension of individuality in the decisions of the agent.

262 citations

Proceedings Article
20 Aug 2000
TL;DR: A particular protocol which is suitable for negotiation is proposed, and its use is illustrated on an example from the literature, showing how the generation and interpretation of arguments fits into the process of negotiation.
Abstract: In the past few years there have been a number of proposals for mechanisms for negotiation between agents that make use of argumentation. These proposals have largely been vague on the subject of how the generation and interpretation of arguments fits into the process of negotiation. This paper addresses this gap, proposing a particular protocol which is suitable for negotiation, and illustrating its use on an example from the literature.

240 citations


Cites background from "A Framework for Argumentation-Based..."

  • ...In recent years, there have been a number of suggestions for systems of negotiation based upon argumentation, including work by Parsons and Jennings [7, 10], Reed [9], Sycara [11] and Tohmé [12]....

    [...]

  • ...Acknowledgements: This work was partially supported by the Commission of the European Communities under contract IST-199910948, Sustainable Lifecycles in Information Ecosystems....

    [...]

Journal ArticleDOI
TL;DR: In this paper, the authors proposed a collaborative filtering system called Tête-à-Tête, which uses similar techniques to recommend complex products based on multiattribute utility theory.
Abstract: tion engine then returns a list of products that satisfy all of the shopper’s hard constraints in order of how well they satisfy the shopper’s soft constraints. Tête-à-Tête uses comparable techniques to recommend complex products based on multiattribute utility theory. However, unlike PersonaLogic, Tête-à-Tête also assists buyers and sellers in the merchant-brokering and negotiation stages. Like PersonaLogic, Firefly (www.firefly.com) and other systems based on collaborative filtering [4] help consumers find products (see Figure 1). However, instead of filtering products based on features, Firefly recommends products through an automated “wordof-mouth” recommendation mechanism called “collaborative filtering.” The system first compares a shopper’s product ratings with those of other shoppers. After identifying the shopper’s “nearest neighbors,” or users with similar taste, the system recommends the products the neighbors rated highly but which the shopper may not yet have rated, possi-

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References
More filters
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TL;DR: By showing that argumentation can be viewed as a special form of logic programming with negation as failure, this paper introduces a general logic-programming-based method for generating meta-interpreters for argumentation systems, a method very much similar to the compiler-compiler idea in conventional programming.

4,386 citations


"A Framework for Argumentation-Based..." refers background or methods in this paper

  • ...For the purpose of this paper we follow Dung [3] in assuming that it is a primitive notion, because our focus is on how to resolve the effect of an attack no matter how it is defined....

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Abstract: The study of computational agents capable of rational behaviour has received a great deal of attention in recent years. Theoretical formalizations of such agents and their implementations have proceeded in parallel with little or no connection between them. Tkis paper explores a particular type of rational agent, a BeliefDesire-Intention (BDI) agent. The primary aim of this paper is to integrate (a) the theoretical foundations of BDI agents from both a quantitative decision-theoretic perspective and a symbolic reasoning perspective; (b) the implementations of BDI agents from an ideal theoretical perspective and a more practical perspective; and (c) the building of large-scale applications based on BDI agents. In particular, an air-trafflc management application will be described from both a theoretical and an implementation perspective.

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Frequently Asked Questions (2)
Q1. What contributions have the authors mentioned in the paper "A framework for argumentation-based negotiation" ?

This paper describes a general framework for negotiation in which agents exchange proposals backed by arguments which summarise the reasons why the proposals should be accepted. 

Further work is required to tie these preferences to notions of rationality, in particular to standard ideas of expected utility. This may be inadequate for some domains, in which case it will be necessary for agents to be able to discuss what rules of inference are appropriate.