Journal:Informatica
Volume 19, Issue 2 (2008), pp. 161–190
Abstract
In this paper, a new multi-criteria decision-making procedure is presented, which captures preferential information in the form of the threshold model. It is based on the ELECTRE-like sorting analysis restricted by the localization principle, which enables high adaptability of the decision model and reduces the cognitive load imposed on the decision-makers. It lays the foundation for the introduction of three concepts that have been previously insufficiently supported by outranking methods – semiautomatic derivation of criteria weights according to the selective effects of discordance and veto thresholds, convergent group consensus seeking, and autonomous multi-agent negotiation. The interdependent principles are justified, and the methodological solutions underlying their implementation are provided.
Journal:Informatica
Volume 17, Issue 1 (2006), pp. 85–94
Abstract
In this paper we consider two logics: temporal logic of common knowledge and temporal logic of common belief. These logics involve the discrete time linear temporal logic operators “next” and “until”. In addition the first logic contains an indexed set of unary modal operators “agent i knows”, the second one contains an indexed set of unary modal operators “agent i believes”. Also the first logic contains the modality of common knowledge and the second one contains the modality of common belief. For these logics we present sequent calculi with an analytic cut rule. The soundness and completeness for these calculi are proved.
Journal:Informatica
Volume 17, Issue 1 (2006), pp. 39–54
Abstract
The asynchronous techniques that exist within the programming with distributed constraints are characterized by the occurrence of the nogood values during the search for the solution. The nogood type messages are sent among the agents with the purpose of realizing an intelligent backtrack and of ensuring the algorithm's completion.
In this article we analyzed the way in which a technique of obtaining efficient nogood values could combine with a technique of storing these values. In other words we try combining the resolvent-based learning technique introduced by Yokoo with the nogood processor technique in the case of asynchrounous weak-commitment search algorithm (AWCS). These techniques refer to the possibility of obtaining efficient nogoods, respectively to the way the nogood values are stored and the later use of information given by the nogoods in the process of selecting a new value for the variables associated to agents. Starting from this analysis we proposed certain modifications for the two known techniques.
We analyzed the situations in which the nogoods are distributed to more nogood processors handed by certain agents. We proposed a solution of distributing the nogood processors to the agents regarding the agents' order, with the purpose of reducing the storing and searching costs. We also analyzed the benefits the combining of nogood processor technique with the resolved-based learning technique could bring to the enhancement of the performance of AWCS technique. Finally, we analyzed the behavior of the techniques obtained in the case of messages filtering.