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Title: Dialogue games that agents play within a society
Author: Nishan C Karunatillake, Nicholas R. Jennings, Iyad Rahwan, and Peter McBurney
Journal: Artificial Intelligence
Volume: 173
Pages: 935--981
Year: 2009
DOI: 10.1016/j.artint.2009.02.002
Abstract: Human societies have long used the capability of argumentation and dialogue to overcome and resolve conflicts that may arise within their communities. Today, there is an increasing level of interest in the application of such dialogue games within artificial agent societies. In particular, within the field of multi-agent systems, this theory of argumentation and dialogue games has become instrumental in designing rich interaction protocols and in providing agents with a means to manage and resolve conflicts. However, to date, much of the existing literature focuses on formulating theoretically sound and complete models for multi-agent systems. Nonetheless, in so doing, it has tended to overlook the computational implications of applying such models in agent societies, especially ones with complex social structures. Furthermore, the systemic impact of using argumentation in multiagent societies and its interplay with other forms of social influences (such as those that emanate from the roles and relationships of a society) within such contexts has also received comparatively little attention. To this end, this paper presents a significant step towards bridging these gaps for one of the most important dialogue game types; namely argumentation-based negotiation (ABN). The contributions are three fold. First, we present a both theoretically grounded and computationally tractable ABN framework that allows agents to argue, negotiate, and resolve conflicts relating to their social influences within a multi-agent society. In particular, the model encapsulates four fundamental elements: (i) a scheme that captures the stereotypical pattern of reasoning about rights and obligations in an agent society, (ii) a mechanism to use this scheme to systematically identify social arguments to use in such contexts, (iii) a language and a protocol to govern the agent interactions, and (iv) a set of decision functions to enable agents to participate in such dialogues. Second, we use this framework to devise a series of concrete algorithms that give agents a set of ABN strategies to argue and resolve conflicts in a multi-agent task allocation scenario. In so doing, we exemplify the versatility of our framework and its ability to facilitate complex argumentation dialogues within artificial agent societies. Finally, we carry out a series of experiments to identify how and when argumentation can be useful for agent societies. In particular, our results show: a clear inverse correlation between the benefit of arguing and the resources available within the context; that when agents operate with imperfect knowledge, an arguing approach allows them to perform more effectively than a non-arguing one; that arguing earlier in an ABN interaction presents a more efficient method than arguing later in the interaction; and that allowing agents to negotiate their social influences presents both an effective and an efficient method that enhances their performance within a society.

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@Article{karunatillake09a,
  author =	 {Nishan C Karunatillake and Nicholas R. Jennings and
                  Iyad Rahwan and Peter McBurney},
  title =	 {Dialogue games that agents play within a society},
  journal =	 {Artificial Intelligence},
  year =	 2009,
  volume =	 173,
  pages =	 {935--981},
  abstract =	 {Human societies have long used the capability of
                  argumentation and dialogue to overcome and resolve
                  conflicts that may arise within their
                  communities. Today, there is an increasing level of
                  interest in the application of such dialogue games
                  within artificial agent societies. In particular,
                  within the field of multi-agent systems, this theory
                  of argumentation and dialogue games has become
                  instrumental in designing rich interaction protocols
                  and in providing agents with a means to manage and
                  resolve conflicts. However, to date, much of the
                  existing literature focuses on formulating
                  theoretically sound and complete models for
                  multi-agent systems. Nonetheless, in so doing, it
                  has tended to overlook the computational
                  implications of applying such models in agent
                  societies, especially ones with complex social
                  structures. Furthermore, the systemic impact of
                  using argumentation in multiagent societies and its
                  interplay with other forms of social influences
                  (such as those that emanate from the roles and
                  relationships of a society) within such contexts has
                  also received comparatively little attention. To
                  this end, this paper presents a significant step
                  towards bridging these gaps for one of the most
                  important dialogue game types; namely
                  argumentation-based negotiation (ABN). The
                  contributions are three fold. First, we present a
                  both theoretically grounded and computationally
                  tractable ABN framework that allows agents to argue,
                  negotiate, and resolve conflicts relating to their
                  social influences within a multi-agent society. In
                  particular, the model encapsulates four fundamental
                  elements: (i) a scheme that captures the
                  stereotypical pattern of reasoning about rights and
                  obligations in an agent society, (ii) a mechanism to
                  use this scheme to systematically identify social
                  arguments to use in such contexts, (iii) a language
                  and a protocol to govern the agent interactions, and
                  (iv) a set of decision functions to enable agents to
                  participate in such dialogues. Second, we use this
                  framework to devise a series of concrete algorithms
                  that give agents a set of ABN strategies to argue
                  and resolve conflicts in a multi-agent task
                  allocation scenario. In so doing, we exemplify the
                  versatility of our framework and its ability to
                  facilitate complex argumentation dialogues within
                  artificial agent societies. Finally, we carry out a
                  series of experiments to identify how and when
                  argumentation can be useful for agent societies. In
                  particular, our results show: a clear inverse
                  correlation between the benefit of arguing and the
                  resources available within the context; that when
                  agents operate with imperfect knowledge, an arguing
                  approach allows them to perform more effectively
                  than a non-arguing one; that arguing earlier in an
                  ABN interaction presents a more efficient method
                  than arguing later in the interaction; and that
                  allowing agents to negotiate their social influences
                  presents both an effective and an efficient method
                  that enhances their performance within a society.},
  url = 	 {http://jmvidal.cse.sc.edu/library/karunatillake09a.pdf},
  cluster = 	 {8180474761643939796},
  doi = 	 {10.1016/j.artint.2009.02.002}
}
Last modified: Wed Mar 9 10:16:58 EST 2011