An Argumentation-Based Approach for Dialog Move Selection

Abstract

Modeling different types of dialog between autonomous agents is becoming an important research issue. Several proposals exist with a clear definition of the dialog protocol, which is the set of rules governing the high level behavior of the dialog. However, things seem different with the notion of strategy. There is no consensus on the definition of a strategy and on the parameters necessary for its definition. Consequently, there are no methodology and no formal models for strategies.This paper argues that a strategy is a decision problem that consists of: i) selecting the type of act to utter at a given step of a dialog, and ii) selecting the content that will accompany the act. The first kind of decision amounts to selecting among all the acts allowed by the protocol, the best option which according to some strategic beliefs of the agent will at least satisfy the most important strategic goals of the agent. The second kind of decision consists of selecting among different alternatives (eg. different offers), the best one that, according to some basic beliefs of the agent, will satisfy the functional goals of the agent. The paper proposes then a formal model based on argumentation for computing on the basis of the above kinds of mental states, the best move (act + content) to play at a given step of the dialog. The model is illustrated through an example of auctions.KeywordsReserve PriceBasic BeliefCurrent PriceStrategic GoalArgumentation FrameworkThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.