During the last decade the notion of agent has gained acceptance within the AI community, mainly due to its adequacy to formalize complex environments. Agents can be thought as active software objects, which may be autonomous and able to perceive, reason, act, and interact with other agents.
When agents interact with each other, a multi-agent system (MAS) arises.Eje: Inteligencia Artificial Distribuida, Aspectos Teóricos de la Inteligencia Artificial y Teoría de la ComputaciónRed de Universidades con Carreras en Informática (RedUNCI

Chesñevar, Carlos Iván

English

Servicio de Difusión de la Creación Intelectual

Formalizing Argument-based Agent Interactionin Electronic InstitutionsCarlos Iván ChesñevarLaboratorio de Investigación y Desarrollo en Inteligencia Artificial (LIDIA)Departamento de Ciencias de la ComputaciónUniversidad Nacional del SurAv. Alem 1253 – B8000CPB Bahía Blanca – ARGENTINATel. +54- 291- 459-5135  Fax  +54-291-459-5136Email: cic@cs.uns.edu.arKeywords:  defeasible argumentation, agent theory,   electronic institutionsInterest area:  Theoretical Aspects of Artificial Intelligence1.  Introduction, motivations and goalsDuring the last decade the notion of agent has gained acceptance within the AI community, mainlydue to its adequacy to formalize complex environments. Agents can be thought as active softwareobjects, which may be autonomous  and able to perceive, reason, act, and interact with other agents.When agents interact with each other,  a multi-agent system (MAS) arises.Recently there has been growing interest in incorporating concepts based on the notion oforganization as part of MAS. Organizational approaches come along with a number of issues to becoped with when dealing with open MAS, such as heterogeneity of the agents involved, trust,exception handling, adaptability to social and structural changes, etc.In order to cope with this situation human societies have created institutions that set and enforcelaws, monitor and respond to emergencies, prevent and recover from disasters, etc. Recent work[SSPJ99, NS96 , PSJ98b, ER+00]  has been focused on the adoption of a similar approach for therealization of open multi-agent systems based on the development of electronic institutions.According to [NS96,ER+00], the notion of electronic institution is founded on three basic concepts:dialogical framework, performative structure and rules of behavior. The dialogical frameworkprovides a context or environment for agent interaction. In dialog-based institutions, agents interactamong each other by means of illocutions, which convey the meaning of the agents’ intentions anddesires. The performative structure stipulates the communication protocol under which theseinteractions will take place. Dialogical actions of agents will have consequences, normally ascommitments that impose constraints on actions these agents might carry out in the future. Finally,behavior rules regulate and delimitate the agents’ behavior.The  notion of interaction among agents can be seen as the kernel of an electronic institution.Interactions that can typically be identified as observable part of the agents’ behavior arecooperation, coordination, collaboration and negotiation among agents. Recent research [PSJ98b,NS96] has highlighted the role of argumentation as a process which underlies different kinds ofinteraction among agents.  In many settings, the exchange of illocutions between  two agents thatcooperate, coordinate, collaborate,  or negotiate can be conceptualized as the presentation of  offersand counter-offers (equivalently, arguments and counter-arguments) in order to determine whether anoriginal proposal (thesis) is accepted or rejected.  The dialogical framework has a natural analogywith a logical framework for defeasible argumentation [SL92, Vre93, PraVre99, CML00]. Protocolsfor defeasible argumentation correspond on its turn with the notion of performative structure in anelectronic institution, and dialectical constraints (e.g. consistency, avoidance of fallaciousargumentation, etc.) have a natural correspondence with the notion of behavior rules.In this context, our research work is oriented towards a formalization of argument-based interactionin electronic institutions by applying different logical models for defeasible argumentation.Formalizing complex social structures in these institutions is crucial for a complete understanding ofmany features, such as hierarchies between agents, temporal constraints, computation with limitedresources, etc.  Such a model would allow to study and analyze the emerging behavior of  intelligent,autonomous agents which may interact  asynchronously with each other.  A useful formalization toolis provided by so-called context-based reasoning, which will be briefly discussed in the next section.2.  Context-based reasoning  in electronic institutionsMost cognitive processes carried out by human beings are context-dependant, i.e. they  depend on theenvironment or context within which they are carried out. In AI, the importance of the notion ofcontext was first postulated by John McCarthy in 1987 as an alternative for formalizing the well-known qualification problem. Later research provided several formal theories for context-basedreasoning,  which contributed to the development of new and more powerful ontologies.Developing a framework for defining electronic institutions is clearly a complex task, in whichseveral separate issues (the role of the agents involved, hierarchies among agents, communicationcapabilities, etc.)  are intertwined. Thus, context-based approaches provide a natural tool forformalizing electronic institutions.Two major approaches related to formalizing context-based reasoning were multi-context systems(MCS) and labelled deductive systems (LDS). Multi-context systems [GS94] allow to define andrelate different formal theories, which interact with each other by means of so-called bridge rules.On the other hand, LDS [Gab96] offer also an attractive approach to formalizing complex logicalsystems, since they allow to characterize the different components involved by using different sortsof labels.   These two approaches complement each other (both of them are based on the idea oflabeled formulas: in MCS, the labels denote contexts, whereas in LDS the label is a wff in a labelinglanguage).In recent work  [PSJ98b] a MCS-based approach was developed for characterizing an argument-basedagent architecture.  In this setting, different contexts are used to represent different components of theagent. This approaches enforces a modular structure with well-defined interfaces, and thus accordswell with good software engineering practice. Later work [SSPJ99] showed that actual implementationscould be developed based on this formal model.3.  Ongoing researchCurrently we are trying to relate existing research on argumentation in electronic institutions  toSDEAR , an LDS-based formal approach developed in [Che01].  SDEAR provides a logical frameworkfor modeling argumentative reasoning for a single agent.One of our aims is to extend these ideas for a multi-agent setting, formalizing this situation under adialogical framework as the one described in [NS96, ER+00]. We contend that a formalization ofdifferent kind of interactions among agents can be achieved by applying an LDS-based approach.Research in this direction is currently being pursued.Bibliography[Che01]  CHESÑEVAR, Carlos -  Formalizing Argumentation Processes as Labelled  DeductiveSystems – PhD Thesis (in Spanish). Universidad Nacional del Sur, March 2001.[CML00] CHESÑEVAR, Carlos,  MAGUITMAN, Ana and LOUI, Ronald -  Logical Models ofArgument -  ACM Computing Surveys, Vol. 2,  Number 2, pp. 337-383, Dec. 2000.[ER+00] ESTEVA, J.A;  RODRIGUEZ, J; ARCOS, L.; SIERRA, C.; GARCIA, P. - FormalisingAgent Mediated Electronic Institutions -  I Catalan Congress on AI  2000,  pp. 29-38.[Gab96]  GABBAY, Dov  - Labelling Deductive Systems (vol.1) Clarendon Press, Oxford, 1996.[GS94]  GIUNCHIGLIA, F. and SERAFINI, L. -  Multilanguage hierarchical (or: how we can dowithout modal logic) – Artificial Intelligence, 65:29-70, 1994.[NS96] NORIEGA, P. and SIERRA, C. - Towards layered dialogical agents -  In Proceedings of theECAI 96 Workshop on Agents Theories,  Architectures and Languages  (1996), pp. 157-171.[PraVre99]  PRAKKEN, Henry and VREESWIJK, Gerhard – Logics for Defeasible Argumentation.In Handbook of Philosophical Logic, Editor D.Gabbay,  Ed. Kluwer  Academic Publisher, 1999.[PSJ98] PARSONS, S. , SIERRA, C. and JENNINGS, N. - Agents that Reason and Negotiate byArguing.  In Journal of Logic and Computation, 8 : 1998, 261-292.[PSJ98b] PARSONS, S. , SIERRA, C. and JENNINGS, N. - Multi-context Argumentative agents. InCommon Sense '98 (The Fourth symposium on  Logical Formalizations of Commonsense Reasoning,)pp. 298-349.[RMGNS00] RODRIGUEZ, A. ;  MARTIN, F.; GARCIA, P.; NORIEGA, P. ; SIERRA, C. -Towards a formal specification of Complex  Social Structures in Multi-agent Systems. LNAI 1624,pp. 284-300.[SSPJ99] SABATER, J.;  SIERRA, C.;  PARSONS, S.; and JENNINGS, N. Using multi-contextsystems to engineer executable agents. In  Proc. 6th   Int.Workshop on Agent Theories Architecturesand Languages (ATAL-99). Orlando, pp. 131-148.[SL92]  SIMARI, Guillermo and LOUI, Ronald -  A Mathematical Treatment of  DefeasibleReasoning and its  Implementation. In Artificial Intelligence 53 (1992), 125-157.[Vre93] VREESWIJK, Gerhard – Studies on Defeasible Argumentation – PhD Thesis – VrijeUniversity, Holland, 1993.

Formalizing argument-based agent interaction in electronic institutions

SEDICI - Repositorio de la UNLP

Formalizing Argument-based Agent Interaction
in Electronic Institutions
Carlos Iván Chesñevar
Laboratorio de Investigación y Desarrollo en Inteligencia Artificial (LIDIA)
Departamento de Ciencias de la Computación
Universidad Nacional del Sur
Av. Alem 1253 – B8000CPB Bahía Blanca – ARGENTINA
Tel. +54- 291- 459-5135  Fax  +54-291-459-5136
Email: cic@cs.uns.edu.ar
Keywords:  defeasible argumentation, agent theory,   electronic institutions
Interest area:  Theoretical Aspects of Artificial Intelligence
1.  Introduction, motivations and goals
During the last decade the notion of agent has gained acceptance within the AI community, mainly
due to its adequacy to formalize complex environments. Agents can be thought as active software
objects, which may be autonomous  and able to perceive, reason, act, and interact with other agents.
When agents interact with each other,  a multi-agent system (MAS) arises.
Recently there has been growing interest in incorporating concepts based on the notion of
organization as part of MAS. Organizational approaches come along with a number of issues to be
coped with when dealing with open MAS, such as heterogeneity of the agents involved, trust,
exception handling, adaptability to social and structural changes, etc.
In order to cope with this situation human societies have created institutions that set and enforce
laws, monitor and respond to emergencies, prevent and recover from disasters, etc. Recent work
[SSPJ99, NS96 , PSJ98b, ER+00]  has been focused on the adoption of a similar approach for the
realization of open multi-agent systems based on the development of electronic institutions.
According to [NS96,ER+00], the notion of electronic institution is founded on three basic concepts:
dialogical framework, performative structure and rules of behavior. The dialogical framework
provides a context or environment for agent interaction. In dialog-based institutions, agents interact
among each other by means of illocutions, which convey the meaning of the agents’ intentions and
desires. The performative structure stipulates the communication protocol under which these
interactions will take place. Dialogical actions of agents will have consequences, normally as
commitments that impose constraints on actions these agents might carry out in the future. Finally,
behavior rules regulate and delimitate the agents’ behavior.
The  notion of interaction among agents can be seen as the kernel of an electronic institution.
Interactions that can typically be identified as observable part of the agents’ behavior are
cooperation, coordination, collaboration and negotiation among agents. Recent research [PSJ98b,
NS96] has highlighted the role of argumentation as a process which underlies different kinds of
interaction among agents.  In many settings, the exchange of illocutions between  two agents that
cooperate, coordinate, collaborate,  or negotiate can be conceptualized as the presentation of  offers
and counter-offers (equivalently, arguments and counter-arguments) in order to determine whether an
original proposal (thesis) is accepted or rejected.  The dialogical framework has a natural analogy
with a logical framework for defeasible argumentation [SL92, Vre93, PraVre99, CML00]. Protocols
for defeasible argumentation correspond on its turn with the notion of performative structure in an
electronic institution, and dialectical constraints (e.g. consistency, avoidance of fallacious
argumentation, etc.) have a natural correspondence with the notion of behavior rules.
In this context, our research work is oriented towards a formalization of argument-based interaction
in electronic institutions by applying different logical models for defeasible argumentation.
Formalizing complex social structures in these institutions is crucial for a complete understanding of
many features, such as hierarchies between agents, temporal constraints, computation with limited
resources, etc.  Such a model would allow to study and analyze the emerging behavior of  intelligent,
autonomous agents which may interact  asynchronously with each other.  A useful formalization tool
is provided by so-called context-based reasoning, which will be briefly discussed in the next section.
2.  Context-based reasoning  in electronic institutions
Most cognitive processes carried out by human beings are context-dependant, i.e. they  depend on the
environment or context within which they are carried out. In AI, the importance of the notion of
context was first postulated by John McCarthy in 1987 as an alternative for formalizing the well-
known qualification problem. Later research provided several formal theories for context-based
reasoning,  which contributed to the development of new and more powerful ontologies.
Developing a framework for defining electronic institutions is clearly a complex task, in which
several separate issues (the role of the agents involved, hierarchies among agents, communication
capabilities, etc.)  are intertwined. Thus, context-based approaches provide a natural tool for
formalizing electronic institutions.
Two major approaches related to formalizing context-based reasoning were multi-context systems
(MCS) and labelled deductive systems (LDS). Multi-context systems [GS94] allow to define and
relate different formal theories, which interact with each other by means of so-called bridge rules.
On the other hand, LDS [Gab96] offer also an attractive approach to formalizing complex logical
systems, since they allow to characterize the different components involved by using different sorts
of labels.   These two approaches complement each other (both of them are based on the idea of
labeled formulas: in MCS, the labels denote contexts, whereas in LDS the label is a wff in a labeling
language).
In recent work  [PSJ98b] a MCS-based approach was developed for characterizing an argument-based
agent architecture.  In this setting, different contexts are used to represent different components of the
agent. This approaches enforces a modular structure with well-defined interfaces, and thus accords
well with good software engineering practice. Later work [SSPJ99] showed that actual implementations
could be developed based on this formal model.
3.  Ongoing research
Currently we are trying to relate existing research on argumentation in electronic institutions  to
SDEAR , an LDS-based formal approach developed in [Che01].  SDEAR provides a logical framework
for modeling argumentative reasoning for a single agent.
One of our aims is to extend these ideas for a multi-agent setting, formalizing this situation under a
dialogical framework as the one described in [NS96, ER+00]. We contend that a formalization of
different kind of interactions among agents can be achieved by applying an LDS-based approach.
Research in this direction is currently being pursued.
Bibliography
[Che01]  CHESÑEVAR, Carlos -  Formalizing Argumentation Processes as Labelled  Deductive
Systems – PhD Thesis (in Spanish). Universidad Nacional del Sur, March 2001.
[CML00] CHESÑEVAR, Carlos,  MAGUITMAN, Ana and LOUI, Ronald -  Logical Models of
Argument -  ACM Computing Surveys, Vol. 2,  Number 2, pp. 337-383, Dec. 2000.
[ER+00] ESTEVA, J.A;  RODRIGUEZ, J; ARCOS, L.; SIERRA, C.; GARCIA, P. - Formalising
Agent Mediated Electronic Institutions -  I Catalan Congress on AI  2000,  pp. 29-38.
[Gab96]  GABBAY, Dov  - Labelling Deductive Systems (vol.1) Clarendon Press, Oxford, 1996.
[GS94]  GIUNCHIGLIA, F. and SERAFINI, L. -  Multilanguage hierarchical (or: how we can do
without modal logic) – Artificial Intelligence, 65:29-70, 1994.
[NS96] NORIEGA, P. and SIERRA, C. - Towards layered dialogical agents -  In Proceedings of the
ECAI 96 Workshop on Agents Theories,  Architectures and Languages  (1996), pp. 157-171.
[PraVre99]  PRAKKEN, Henry and VREESWIJK, Gerhard – Logics for Defeasible Argumentation.
In Handbook of Philosophical Logic, Editor D.Gabbay,  Ed. Kluwer  Academic Publisher, 1999.
[PSJ98] PARSONS, S. , SIERRA, C. and JENNINGS, N. - Agents that Reason and Negotiate by
Arguing.  In Journal of Logic and Computation, 8 : 1998, 261-292.
[PSJ98b] PARSONS, S. , SIERRA, C. and JENNINGS, N. - Multi-context Argumentative agents. In
Common Sense '98 (The Fourth symposium on  Logical Formalizations of Commonsense Reasoning,)
pp. 298-349.
[RMGNS00] RODRIGUEZ, A. ;  MARTIN, F.; GARCIA, P.; NORIEGA, P. ; SIERRA, C. -
Towards a formal specification of Complex  Social Structures in Multi-agent Systems. LNAI 1624,
pp. 284-300.
[SSPJ99] SABATER, J.;  SIERRA, C.;  PARSONS, S.; and JENNINGS, N. Using multi-context
systems to engineer executable agents. In  Proc. 6th   Int.Workshop on Agent Theories Architectures
and Languages (ATAL-99). Orlando, pp. 131-148.
[SL92]  SIMARI, Guillermo and LOUI, Ronald -  A Mathematical Treatment of  Defeasible
Reasoning and its  Implementation. In Artificial Intelligence 53 (1992), 125-157.
[Vre93] VREESWIJK, Gerhard – Studies on Defeasible Argumentation – PhD Thesis – Vrije
University, Holland, 1993.


http://sedici.unlp.edu.ar/bitstream/handle/10915/21635/Documento_completo.pdf?sequence=1

Formalizing argument-based agent interaction in electronic institutions

Abstract

Similar works

Full text

Available Versions

Servicio de Difusión de la Creación Intelectual

SEDICI - Repositorio de la UNLP