We propose cognitive design patterns (CDPs) as a general methodology to design distributed artificial systems capable of cognitive processing. CDPs are reusable solutions that leverage the current understanding of cognitive processing in natural distributed systems, and that put this knowledge in use for the design of artificial ones [2]. In this paper, we derive a CDP for collective decision m...

Decision-making under uncertainty is a natural part of everyday life of every human being. In societal science, various aspects of decision-making were studied, mostly in the area of psychology. In technical science, the process was formalized using probability theory yielding so called Bayesian theory of decision making (Berger, 1985). However, one of the key assumptions of this theory is that...

Our research addresses issues of design and implementation of a framework and architecture for distributed decision making. While decision support technologies have been studied for a number of years the emergence of new standards and internet technologies provides us with an opportunity to address current problems in distributed and collaborative decision making. This class of problems has bec...

The paper outlines a new challenging area of control, namely distributed decision making under uncertainty. Presence of many decision-making units, called the participants is the main distinction from the classical control theory. The problem is analysed from Bayesian point of view. Each participant has the abilities of classical adaptive controller, i.e. learning of the environment and design ...

Automated negotiation systems with self-interested agents are becoming increasingly important. One reason for this is the technology push of a growing standardized which separately designed agents belonging to diierent organizations can interact in an open environment in real-time and safely carry out transactions. The second reason is strong application pull for computer support for negotiatio...

This paper considers group decision making by imperfect agents that only know quantized prior probabilities for use in Bayesian likelihood ratio tests. Global decisions are made by information fusion of local decisions, but information sharing among agents before local decision making is forbidden. The quantization scheme of the agents is investigated so as to achieve the minimum mean Bayes ris...

For many military and civilian large-scale, real-world problems of interest, data is first acquired asynchronously, i.e., at irregular intervals of time, at geographically-dispersed sites, processed utilizing decision-making algorithms, and the processed data then disseminated to other appropriate sites. Examples include the battlefield where intelligence data is gathered from different sources...

The paper presents several practical issues concerning the multi-participant decision-making processes with emphasis on crowdsourcing approach. development of effective modern telecom systems that enable operations decision units are detailed. System scalability and operator’s agility to incorporate continuous changing technologies chal-lenge further research.