Title of article :
Audiences in argumentation frameworks Original Research Article
Author/Authors :
Trevor J.M. Bench-Capon، نويسنده , , Marie-Sylvie Doutre، نويسنده , , Paul E. Dunne، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2007
Abstract :
Although reasoning about what is the case has been the historic focus of logic, reasoning about what should be done is an equally important capacity for an intelligent agent. Reasoning about what to do in a given situation—termed practical reasoning in the philosophical literature—has important differences from reasoning about what is the case. The acceptability of an argument for an action turns not only on what is true in the situation, but also on the values and aspirations of the agent to whom the argument is directed. There are three distinctive features of practical reasoning: first, that practical reasoning is situated in a context, directed towards a particular agent at a particular time; second, that since agents differ in their aspirations there is no right answer for all agents, and rational disagreement is always possible; third, that since no agent can specify the relative priority of its aspirations outside of a particular context, such prioritisation must be a product of practical reasoning and cannot be used as an input to it. In this paper we present a framework for practical reasoning which accommodates these three distinctive features. We use the notion of argumentation frameworks to capture the first feature. An extended form of argumentation framework in which values and aspirations can be represented is used to allow divergent opinions for different audiences, and complexity results relating to the extended framework are presented. We address the third feature using a formal description of a dialogue from which preferences over values emerge. Soundness and completeness results for these dialogues are given.
Keywords :
Argumentation frameworks , Practical reasoning , Dialogue
Journal title :
Artificial Intelligence
Journal title :
Artificial Intelligence