IBoNN: Intelligent Agent-based Internet of Medical Things framework for detecting brain response from Electroencephalography signal using Bag-of-Neural Network

2022 ◽  
Author(s):  
Sudarshan Nandy ◽  
Mainak Adhikari ◽  
Supriya Chakraborty ◽  
Ahmed Alkhayyat ◽  
Neeraj Kumar
Keyword(s):  
Neural Network ◽  
Intelligent Agent ◽  
Brain Response ◽  
Agent Based ◽  
Internet Of Medical Things

scholarly journals Black-Box-Based Mathematical Modelling of Machine Intelligence Measuring

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 681
Author(s):  
László Barna Iantovics
Keyword(s):  
Problem Solving ◽  
Scientific Literature ◽  
Real Life ◽  
Intelligent Agent ◽  
Difficult Problem ◽  
Black Box ◽  
Machine Intelligence ◽  
Agent Based ◽  
Np Hard Problem ◽  
Box Method

Current machine intelligence metrics rely on a different philosophy, hindering their effective comparison. There is no standardization of what is machine intelligence and what should be measured to quantify it. In this study, we investigate the measurement of intelligence from the viewpoint of real-life difficult-problem-solving abilities, and we highlight the importance of being able to make accurate and robust comparisons between multiple cooperative multiagent systems (CMASs) using a novel metric. A recent metric presented in the scientific literature, called MetrIntPair, is capable of comparing the intelligence of only two CMASs at an application. In this paper, we propose a generalization of that metric called MetrIntPairII. MetrIntPairII is based on pairwise problem-solving intelligence comparisons (for the same problem, the problem-solving intelligence of the studied CMASs is evaluated experimentally in pairs). The pairwise intelligence comparison is proposed to decrease the necessary number of experimental intelligence measurements. MetrIntPairII has the same properties as MetrIntPair, with the main advantage that it can be applied to any number of CMASs conserving the accuracy of the comparison, while it exhibits enhanced robustness. An important property of the proposed metric is the universality, as it can be applied as a black-box method to intelligent agent-based systems (IABSs) generally, not depending on the aspect of IABS architecture. To demonstrate the effectiveness of the MetrIntPairII metric, we provide a representative experimental study, comparing the intelligence of several CMASs composed of agents specialized in solving an NP-hard problem.

An ontology, intelligent agent-based framework for the provision of semantic web services

2009 ◽  
Vol 36 (2) ◽  
pp. 3167-3187 ◽  
Author(s):  
Francisco García-Sánchez ◽  
Rafael Valencia-García ◽  
Rodrigo Martínez-Béjar ◽  
Jesualdo T. Fernández-Breis
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Intelligent Agent ◽  
Semantic Web Services ◽  
Agent Based

scholarly journals ПІДХОДИ ДО СТВОРЕННЯ ПРОГРАМНОГО АГЕНТА НА ОСНОВІ МЕТАЕВРИСТИК І ШТУЧНИХ НЕЙРОННИХ МЕРЕЖ

2019 ◽  
pp. 58-65
Author(s):  
Євген Євгенович Федоров ◽  
Марина Володимирівна Чичужко ◽  
Владислав Олегович Чичужко
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Internal State ◽  
Numerical Study ◽  
Agent Based ◽  
Development Framework ◽  
Number Of Visits ◽  
Artificial Neural ◽  
The Creation ◽  
Elman Recurrent Neural Network

In this article, has been developed a software agent based on meta-heuristics and artificial neural networks. The analysis of existing classes of agents and the selected reactive agent with internal state, which is well suited for partially observable, dynamic and non-episodic media, was carried out, and this agent has an internal state that preserves the state of the environment, obtained on the basis of the history of acts of perception, in the form of structured data. Were proposed approaches to create an agent based on meta-heuristics and an agent based on an artificial neural network. The development of reactive agents with internal state, based on the PSO (particle swarm optimization) metaheuristics, which are related to individual particles and to a whole swarm and interact by messages was proposed. Also, has been proposed an approach to the creation of a reactive agent with an internal state based on the Elman recurrent neural network. The agent-based approach allows combining different areas of artificial intelligence, digital signal processing, mathematical modeling, and game theory. The proposed agents were implemented using the JADE (Java Agent Development Framework) toolkit, which is one of the most popular tools for the creation of agent systems. A numerical study was made to determine the parameters of the swarm PSO metaheuristics and the Elman recurrent neural network. As a purpose function, the Rastrigin test function has been used. The number of visits to the website of DonNTU was used as an input sample for the Elman network. The minimum average square error forecast was the criterion for choosing the structure of a network model. 10 hiding neurons were used to predict the number of visits to the website page, since, with increasing of hidden neurons number, the change in the error value is small. To determine the number of particles in the swarm, a series of experiments was conducted, the results of which are presented by graphs. The proposed approaches can be used in intelligent computer systems.

scholarly journals Agent-based Modeling in doing Logic Programming in Fuzzy Hopfield Neural Network

2021 ◽  
Vol 13 (2) ◽  
pp. 23-32
Author(s):  
Shehab Abdulhabib Saeed Alzaeemi ◽  
◽  
Saratha Sathasivam ◽  
Muraly Velavan
Keyword(s):  
Neural Network ◽  
Logic Programming ◽  
Hopfield Neural Network ◽  
Agent Based Modeling ◽  
Agent Based

scholarly journals Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
S. Ganapathy ◽  
P. Yogesh ◽  
A. Kannan
Keyword(s):  
Intrusion Detection ◽  
False Alarm ◽  
False Alarm Rate ◽  
Outlier Detection ◽  
Intelligent Agent ◽  
Support Vector ◽  
Detection Accuracy ◽  
Data Set ◽  
Agent Based ◽  
Multiclass Svm

Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set.

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