Dealing with Incompatibilities among Procedural Goals under Uncertainty


  • Mariela Morveli Espinoza Universidade Tecnológica Federal do Paraná
  • Juan Carlos Nieves University of Umea
  • Ayslan Possebom Federal Institute of Parana
  • Cesar Augusto Tacla Federal University of Technology of Parana



Argumentation, Goals selection, Uncertainty, Arguments strength, goals conflicts


By considering rational agents, we focus on the problem of selecting goals out of a set of incompatible ones. We consider three forms of incompatibility introduced by Castelfranchi and Paglieri, namely the terminal, the instrumental (or based on resources), and the superfluity. We represent the agent's plans by means of structured arguments whose premises are pervaded with uncertainty. We measure the strength of these arguments in order to determine the set of compatible goals. We propose two novel ways for calculating the strength of these arguments, depending on the kind of incompatibility that
exists between them. The first one is the logical strength value, it is denoted by a three-dimensional vector, which is calculated from a probabilistic interval associated with each argument. The vector represents the precision of the interval, the location of it, and the combination of precision and location. This type of representation and treatment of the strength of a structured argument has not been defined before by the state of the art. The second way for calculating the strength of the argument is based on the cost of the plans (regarding the necessary resources) and the preference of the goals associated with the plans. Considering our novel approach for measuring the strength of structured arguments, we propose a semantics for the selection of plans and goals that is based on Dung's abstract argumentation theory. Finally, we make a theoretical evaluation of our proposal.


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How to Cite

Morveli Espinoza, M., Nieves, J. C., Possebom, A., & Tacla, C. A. (2019). Dealing with Incompatibilities among Procedural Goals under Uncertainty. Inteligencia Artificial, 22(64), 47–62.