Argumentation based modeling of decision aiding for autonomous agents
Yannis Dimopoulos, Pavlos Moraı̈tis, Alexis Tsoukiàs · 2004
Decision Aiding can be abstractly described as the pro-cess of assisting a user/client/decision maker by recom-mending possible courses of his action. This process has to be able to cope with incomplete and/or inconsistent infor-mation for the following reasons. First, the recommenda-tions provided during this process depend heavily on the en-vironment the decision is made. Since complete knowledge of this environment is almost impossible, decision aiding has to be carried out under incomplete information. Sec-ond, the decision aiding process also depends on the pref-erences of its user. However, such subjective information is affected by uncertainty, possible inconsistencies and is dynamically revised due to the time dimension of decision aiding. A complete description of a model of the user is also almost impossible, therefore a decision aiding process must also account for this source of incompletness. This paper presents a model of Decision Aiding that is amenable to au-tomation and shows how it can be embedded in autonomous agents and thus give them the capability to provide deci-sion aiding to a human user or to completely substitute him for some decision task. The whole process is modelled in an suitable argumentation framework that treats Decision Aiding as an iterative defeasible reasoning process. 1