Intelligent Decision Technologies
About: Intelligent Decision Technologies is an academic journal published by IOS Press. The journal publishes majorly in the area(s): Computer science & Artificial intelligence. It has an ISSN identifier of 1872-4981. Over the lifetime, 869 publications have been published receiving 3959 citations.
Topics: Computer science, Artificial intelligence, Decision support system, Deep learning, Fuzzy logic
Papers published on a yearly basis
TL;DR: A state-of-the-art of virtual human architecture is presented mentioning about the use of intelligent decision technologies in order to build virtual human architectures, and various aspects such as autonomy, interaction and personification are considered.
Abstract: Intelligent virtual characters has been subject to exponential growth in the last decades and they are utilized in many application areas such as education, training, human-computer interfaces and entertainment. In this paper, we present a state-of-the-art of virtual human mentioning about the use of intelligent decision technologies in order to build virtual human architectures. We consider various aspects such as autonomy, interaction and personification. Each of these aspects comes to prominence in different applications. This survey provides a novel insight to the current state of designing and modeling virtual humans using different decision technologies and can be used as a basis for several future directions.
TL;DR: A technique is proposed that stores the previously encountered operational situations in a fuzzy rule database that provides smooth and fast convergence and prevents the concept and weight values from being saturated.
Abstract: In this paper, we present a general computational and operational framework for the Fuzzy Cognitive Network FCN, which is a direct extension of Fuzzy Cognitive Maps FCM. The proposed framework assumes a network operation, which continuously receives feedback from the system it describes and outputs control or decision values. This way, its knowledge is continuously updated making it suitable for adaptive decision making or even for adaptive control tasks. The interconnection weights are continuously updated based on a modified delta rule that provides smooth and fast convergence and prevents the concept and weight values from being saturated. To avoid intensive interference of the updating mechanism with the real system, a technique is proposed that stores the previously encountered operational situations in a fuzzy rule database. The explanation of the proposed methodology is interweaved with the FCN description of a simulated hydro-electric plant, which is also used for the experimental results. The proposed framework can be used both for on-line control and decision making tasks.
TL;DR: This paper proposes an efficient realization of 2-to-1 multiplexer using memristors and presents a synthesis methodology that represents a given Boolean function as a Reduced Ordered Binary Decision Diagram (ROBDD) and then maps the same to memristor implementation.
Abstract: Very recently a new passive circuit element called memristor has been extensively investigated by researchers, which can be used for a variety of applications. This two-terminal device having few nanometer dimensions has been experimentally shown to possess both memory and resistor properties. This has also received great attention due to the fact that these devices can very easily be integrated on CMOS subsystems. Most of the logic design works in this context are based on material implication operation which can be very efficiently implemented using memristors. In this paper we propose an efficient realization of 2-to-1 multiplexer using memristors, and hence present a synthesis methodology that represents a given Boolean function as a Reduced Ordered Binary Decision Diagram (ROBDD) and then maps the same to memristor implementation.