Roberto Confalonieri
This STMS has taken place at the Institut de Recherche en Informatique de Toulouse (IRIT) of Université Paul Sabatier in Toulouse, France from January 3rd until January 31st.
The scientific goal of this STSM has been to investigate the development of an Answer Set Programming (ASP)-based methodology for handling Qualitative Decisions under Uncertainty.
In fact Existing Answer Set Programming (ASP)-based methodologies for handling decision making problems amount to compile a decision problem as a logic program able to generate the space of possible decision solutions and to specify an order between them by means of an ordered disjunction connective. Although such approaches are enough to cover decisions in completely certain environment, they become less effective when the knowledge is pervaded with uncertainty.
On the other hand, the decision under uncertainty problem with qualitative preferences and uncertainty has been studied in the setting of possibility theory and, as in classical utility theory, pessimistic and optimistic criteria have been proposed and justified on the basis of postulates. In the STSM an Answer Set Programming (ASP)-based method has been investigated for modeling decision problems and computing optimal decisions in the sense of the possibilistic criteria. This has been achieved by applying both a classic and a possibilistic ASP-based methodology.
Such research work has led to the writing of a research article ready to be submitted.
This STMS has taken place at the Institut de Recherche en Informatique de Toulouse (IRIT) of Université Paul Sabatier in Toulouse, France from January 3rd until January 31st.
The scientific goal of this STSM has been to investigate the development of an Answer Set Programming (ASP)-based methodology for handling Qualitative Decisions under Uncertainty.
In fact Existing Answer Set Programming (ASP)-based methodologies for handling decision making problems amount to compile a decision problem as a logic program able to generate the space of possible decision solutions and to specify an order between them by means of an ordered disjunction connective. Although such approaches are enough to cover decisions in completely certain environment, they become less effective when the knowledge is pervaded with uncertainty.
On the other hand, the decision under uncertainty problem with qualitative preferences and uncertainty has been studied in the setting of possibility theory and, as in classical utility theory, pessimistic and optimistic criteria have been proposed and justified on the basis of postulates. In the STSM an Answer Set Programming (ASP)-based method has been investigated for modeling decision problems and computing optimal decisions in the sense of the possibilistic criteria. This has been achieved by applying both a classic and a possibilistic ASP-based methodology.
Such research work has led to the writing of a research article ready to be submitted.