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Book ChapterDOI

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
Book ChapterDOI
25 Dec 2008
TL;DR: This paper provides a logical framework of negotiating agents who have capabilities of evaluating and building proposals, and develops a method for computing proposals using answer set programming.
Abstract: This paper provides a logical framework of negotiating agents who have capabilities of evaluating and building proposals. Given a proposal, an agent decides whether it is acceptable or not. If the proposal is unacceptable as it is, the agent seeks conditions to accept it. This attitude is captured as a process of making hypotheses by induction . If an agent fails to find a hypothesis, it would concede by giving up some of its current belief. This attitude is characterized using default reasoning . We provide a logical framework of such think-act cycle of an agent, and develop a method for computing proposals using answer set programming .

6 citations

Dissertation
01 Jan 2011
TL;DR: This thesis proposes a novel combination of techniques that takes into consideration the policies that others may be operating with, and presents an agent decision-making mechanism where models of other agents are used to guide future argumentation strategy.
Abstract: In many settings, agents (whether human or artificial) engage in problem solving activities, which require them to share resources, act on each others’ behalf, communicate and coordinate individual acts, and so on. If autonomous agents are to effectively interact (or support interaction among humans) in situations such as deciding whom and how to approach the provision of a resource or the performance of an action, there are a number of important questions to address. Who do I choose to delegate a task to? What do I need to say to convince him/her to do something? Were similar requests granted from similar agents in similar circumstances? What arguments were most persuasive? What are the costs involved in putting certain arguments forward? Research in argumentation strategies has received significant attention in recent years, and a number of approaches has been proposed to enable agents to reason about arguments to put forward in order to persuade another. However, current approaches do not adequately address situations where agents may be operating under social constraints (e.g., policies) that regulate behaviour in a society. Furthermore, existing approaches are largely theoretical, lacking rigorous empirical evaluation. In this thesis, we propose a novel combination of techniques that takes into consideration the policies that others may be operating with. First, we present an approach where evidence derived from argumentation-based dialogue is utilised to learn the policies that others may be operating under. We show that this approach enables agents to build more accurate and stable models of others more rapidly. In addition, we demonstrate how background knowledge can be utilised to further refine such models. Secondly, we present an agent decision-making mechanism where models of other agents are used to guide future argumentation strategy. This approach takes into account the learned policy constraints of others, the cost of revealing information, and anticipated resource availability in deciding whom to approach for a resource or for an action to be done. Furthermore, we present a number of strategies that an agent can employ during such interactions. We empirically evaluate our approach within a simulated multi-agent framework, and demonstrate that through the use of such informed strategies agents can both significantly improve the cumulative utility of dialogical outcomes, and reduce communication overhead.

6 citations


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

  • ..., 2003; Black and Atkinson, 2011), argument evaluation (Sierra et al., 1998; Parsons et al., 1998), and conflict resolution (Jung et al....

    [...]

Book ChapterDOI
01 Jan 2008
TL;DR: This paper proposes both linear and non-linear approaches for partner selection in multi-agent systems with the proposed extended dual model, which is sensitive to changes of the negotiation environment, so they can be adopted in open and dynamic negotiation environments.
Abstract: Traditional negotiation approaches pay intensive attention to decision making models in order to reach the optimal agreements, while placing insufficient efforts on the problem of partner selection. In open and dynamic environments, when the number of potential partners is huge, it may be expensive or even impractical to perform complicated negotiations with all of its potential partners. In this paper, based on the proposed extended dual model, we propose both linear and non-linear approaches for partner selection in multi-agent systems. By employing these two approaches with the extended dual concern model, agents can adapt their individual behaviors for partners selection in negotiation. The proposed approaches have three merits, which are: (1) both agents' own benefits and their potential partners' benefits are considered during the partners selection process; (2) agents' preferences are employed by the proposed approaches which ensure the selection results to accord with agents' expectations; (3) the proposed approaches are sensitive to changes of the negotiation environment, so they can be adopted in open and dynamic negotiation environments. According to the case study in four scenarios, the selection results are reasonable and accord with agents' expectations.

6 citations

Book
22 Mar 2002
TL;DR: This proposal connects a model for the collective analysis of agent systems with an individual-based model that leads on to a virtuous cycle in which individual behaviours can be mapped on to global models and vice-versa.
Abstract: Two key issues in building multi-agent systems concern their scalability and engineering open systems. We offer solutions to these potential problems by introducing a lifecycle for models of large multi-agent systems. Our proposal connects a model for the collective analysis of agent systems with an individual-based model. This approach leads on to a virtuous cycle in which individual behaviours can be mapped on to global models and vice-versa. We illustrate our approach with a formal example but relatively easy for engineers to follow and adapt.

6 citations


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

  • ...Negotiation [16] and argumentation [21], for instance, are two examples of interactions that are essentially and intrinsically performed among individuals....

    [...]

Dissertation
01 Jan 2009
TL;DR: In this article, a model of negociación is proposed to represent the preferencias de agentes, the especificacion del protocol de interaccion que gobierna the negociacion, and the diseno de estrategias heuristicas for negociation automatica.
Abstract: espanolPodemos entender la negociacion como una interaccion entre varias partes que intentan alcanzar un acuerdo en relacion a una serie de atributos que les suponen un conflicto de intereses. Asi definida, la negociacion esta presente en numerosos aspectos de la vida cotidiana, desde las relaciones personales a la economia o la politica internacional. Algunos escenarios de negociacion pueden ser total o parcialmente automatizados, beneficiandose asi de las ventajas en cuanto a eficiencia del empleo de tecnicas de inteligencia artificial. Entre los problemas que ya se han abordado con exito en la literatura haciendo uso de negociacion automatica entre agentes podemos destacar diferentes escenarios de negociacion en comercio electronico y problemas de reparto de recursos o tareas, como por ejemplo cadenas de produccion o reparto de carga computacional en procesos informaticos. La automatizacion de los procesos de negociacion permite no solo replicar la toma de decisiones humana en escenarios de negociacion tradicionales, sino tambien abordar problemas en los que la negociacion con humanos no es viable, ya sea por la complejidad del escenario o por las limitaciones temporales del proceso de negociacion. Dentro de este ambito, existe un interes creciente por el estudio de escenarios de negociacion complejos, como pueden ser las negociaciones de contratos juridicos o los acuerdos de requisitos entre proveedores y clientes. En este tipo de escenarios, son frecuentes las negociaciones de multiples atributos interdependientes. La complejidad inherente a este tipo de problemas de negociacion sugiere la automatizacion total o parcial del proceso, especialmente cuando existen restricciones temporales severas sobre la duracion de la negociacion. Sin embargo, la dependencia entre atributos genera espacios de utilidad no lineales, haciendo que los mecanismos clasicos de negociacion automatica no sean aplicables. Incluso mecanismos especificamente disenados para escenarios no lineales pueden fallar si la complejidad del espacio de utilidades aumenta considerablemente. Existe, por tanto, la necesidad de disenar mecanismos que permitan negociar de forma efectiva y eficaz en escenarios que impliquen espacios de utilidad de elevada complejidad. Esta tesis aborda el problema de la negociacion automatica multilateral en espacios de utilidad complejos, tratando de dar respuesta a esta necesidad. Para ello se propone un modelo de negociacion especialmente disenado para este tipo de escenarios. El modelo comprende la representacion de las preferencias de los agentes, la especificacion del protocolo de interaccion que gobierna la negociacion, y el diseno de estrategias heuristicas para la toma de decisiones de los agentes. Para las preferencias de los agentes, se opta por funciones de utilidad basadas en restricciones ponderadas, y se presenta un generador de preferencias que permite disenar, a partir de un conjunto de parametros, escenarios de complejidad ajustable, tanto en lo referente a la complejidad de los espacios de preferencias individuales de los agentes como en lo referente a la correlacion mutua de las funciones de utilidad de los diferentes agentes. Para el proceso de negociacion, este trabajo parte de la hipotesis de que, en escenarios en los que los espacios de utilidad de los agentes son complejos, la dificultad de la consecucion de acuerdos mutuamente aceptables puede paliarse buscando un equilibrio adecuado entre los objetivos individuales de maximizacion de la utilidad de cada agente, y el objetivo social de la consecucion del acuerdo. Teniendo esto en cuenta, se propone un protocolo de interaccion expresivo e iterativo basado en subastas, que permite a los agentes refinar sus propuestas en cada iteracion sirviendose de la capacidad expresiva que proporcionan las tecnicas de argumentacion. Finalmente, se disena un conjunto de estrategias para la toma de decisiones de los agentes, orientadas a equilibrar el beneficio obtenido y la probabilidad de acuerdo en funcion de la actitud hacia el riesgo de cada agente. Una vez formulada la propuesta, se ha realizado una exhaustiva evaluacion experimental orientada a determinar la contribucion a la negociacion de los mecanismos propuestos en terminos de efectividad y eficiencia. Los experimentos realizados han confirmado nuestra hipotesis de trabajo y la adecuacion de nuestra propuesta basada en el equilibrio entre utilidad y probabilidad de acuerdo y la capacidad expresiva de los agentes, y nos han permitido extraer importantes conclusiones en el ambito de investigacion de los sistemas de negociacion automatica multilateral multiatributo para espacios de utilidad complejos. EnglishWe can see negotiation as an interaction between two or more parties who intend to reach an agreement about a range of issues which requires to solve a conflict of interests between them. As such, negotiation is present in vastly different aspects of our everyday lives, from personal relationships to economy or international politics. Some negotiation scenarios can be fully or partially automated, thus taking advantage of the efficiency of artificial intelligence techniques. Among the problems which have been successfully adressed in the literature using negotiation, we can cite different negotiation scenarios in e-commerce, and resource or task allocation problems, such as manufacturing chains or load balancing in computing processes. Automatization of negotiation processes allows not only to emulate human negotiation in traditional scenarios, but also to address problems where human negotiation is not feasible, due to the complexity of the scenario, or due to the time constraints over the negotiation process. In this context, there is an increasing research interest in complex negotiation scenarios, such as legal contract negotiations or service level agreements between customers and providers. In these scenarios, negotiations often involve multiple, interdependent issues. The complexity of these problems suggest the partial or full automatization of the process, specially when there are hard negotiation deadlines. However, issue interdependency results in nonlinear utility spaces, making classic negotiation mechanisms not applicable. Even mechanisms specifically designed for nonlinear scenarios may fail when the complexity of the utility spaces increases. Therefore, alternative mechanisms are needed which allow to negotiate in an effective and efficient manner in scenarios involving highly complex utility spaces. This PhD thesis addresses the problem of multilateral automated negotiation for complex utility spaces, in an attempt to fulfil this need. To this end, a negotiation model is proposed, which is specifically designed for these scenarios. The model comprises the representation of the agents’ preferences, the specification of the interaction protocol which governs the negotiation, and the design of heuristic strategies for agent decision making. For agent preferences, constraint based utility functions are chosen, and we present a preference generator which allows to define, giving a set of generation parameters, scenarios of adjusted complexity, both regarding the complexity of the individual agent utility spaces and the corelation between different agents’ utility functions. For the negotiation process, our hypothesis is that, in scenarios involving complex utility spaces, we can improve the process of finding mutually acceptable agreements by balancing the utility-maximizing goals of each individual agent and the social goal of reaching an agreement. Taking this into account, we propose an expressive, iterative, auction-based negotiation protocol, which allows agents to refine their bids at each iteration, making use of the expressive capabilities provided by argumentation techniques. Finally, a set of strategies for agent decision making is proposed. These strategies are intended to balance expected utility and deal probability considering the risk attitudes of the different agents. Once the proposal has been made, an exhaustive experimental evaluation is performed to assess the contribution of the proposed mechanisms in terms of effectiveness and efficiency. Experiments have confirmed our hypothesis and the suitability of our proposal based on the balance between utility and deal probability and the expressive capabilities of the agents, allowing us to draw important conclusions on the field of multilateral, multi-issue automated negotiation for complex utility spaces.

6 citations

References
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Journal ArticleDOI
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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  • ...Fundamental to this view of decision making is the idea that one argument may attack another [3]....

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01 Jan 1995
TL;DR: This paper explores a particular type of rational agent, a BeliefDesire-Intention (BDI) agent, and integrates the theoretical foundations of BDI agents from both a quantitative decision-theoretic perspective and a symbolic reasoning perspective.
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.

3,050 citations


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

  • ...3 In keeping with the spirit of specifying a framework which is neutral with respect to the agent architecture, we do not commit to any specific formal language but note that could be as simple as a propositional language or as elaborate as a multi-modal BDI logic [10,14]....

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Book
01 Jan 1988

781 citations


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

  • ...If some additional criteria must be applied to decide which to keep, for instance epistemic entrenchment [4]....

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Journal ArticleDOI
01 Jan 1981
TL;DR: Two forms of cooperation in distributed problem solving are considered: task-sharing and result-sharing, and the basic methodology is presented and systems in which it has been used are described.
Abstract: Two forms of cooperation in distributed problem solving are considered: task-sharing and result-sharing. In the former, nodes assist each other by sharing the computational load for the execution of subtasks of the overall problem. In the latter, nodes assist each other by sharing partial results which are based on somewhat different perspectives on the overall problem. Different perspectives arise because the nodes use different knowledge sources (KS's) (e.g., syntax versus acoustics in the case of a speech-understanding system) or different data (e.g., data that is sensed at different locations in the case of a distributed sensing system). Particular attention is given to control and to internode communication for the two forms of cooperation. For each, the basic methodology is presented and systems in which it has been used are described. The two forms are then compared and the types of applications for which they are suitable are considered.

681 citations


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

  • ...These proposals can then either be accepted or rejected as is the case in the contract net protocol [16], for instance....

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Book
01 Jan 1994

655 citations

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.