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		Expertness framework in multi-agent systems and its application in credit assignment problem
, Article Intelligent Data Analysis ; Vol. 18, issue. 3 , 2014 , p. 511-528 ; Beigy, H ; Sharif University of Technology
								
								
					2014
				
							
				
		
							Abstract
				
					
			
		
										
				One of the challenging problems in artificial intelligence is credit assignment which simply means distributing the credit among a group, such as a group of agents. We made an attempt to meet this problem with the aid of the reinforcement learning paradigm. In this paper, expertness framework is defined and applied to the multi-agent credit assignment problem. In the expertness framework, the critic agent, who is responsible for distributing credit among agents, is equipped with learning capability, and the proposed credit assignment solution is based on the critic to learn to assign a proportion of the credit to each agent, and the used proportion should be learned by reinforcement... 
				
				
				
					Critic learning in multi agent credit assignment problem
, Article Journal of Intelligent and Fuzzy Systems ; Volume 30, Issue 6 , 2016 , Pages 3465-3480 ; 10641246 (ISSN) ; Beigy, H ; Sharif University of Technology
								
					IOS Press 
				
								
								
					2016
				
							
				
		
							Abstract
				
					
			
		
										
				Multi-agent systems can be seen as an apparatus for testing the performance of real distributed systems. One problem encountered in multi-agent systems with the learning capability is credit assignment. This paper presents two methods for solving this problem. The first method assigns credit to the agents according to the history of the interaction while the second method assigns credit to the agents according to the knowledge of agents, and thus the shares of the agents are extracted from the feedback of the environment. The computer experiments show that critic learning has a positive impact in credit assignment problem  
				
				
				
					Addition of learning to critic agent as a solution to the multi-agent credit assignment problem
, Article ICSCCW 2009 - 5th International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, 2 September 2009 through 4 September 2009 ; 2009 ; 9781424434282 (ISBN) ; Beigy, H ; Sharif University of Technology
								
								
					2009
				
							
				
		
							Abstract
				
					
			
		
										
				Multi-agent systems (MAS) is a solution to the nowadays encountered problems, which have the characteristics such as distributiveness, dynamism and the need to adaptation, robustness, efficiency, and reusability. This paper proposed a solution to multi-agent credit assignment problem. The contribution is to equip the critic agent (who is responsible for distributing reinforcements among agents) with learning capability. Some criteria are used to propose an inner feedback to the critic. Results of simulation show the applicability of the method to a task, which has the characteristic that the agent has to decide from a large set of actions. The research is a preliminary step to more in-depth... 
				
				
				
					Toward a solution to multi-agent credit assignment problem
, Article SoCPaR 2009 - Soft Computing and Pattern Recognition, 4 December 2009 through 7 December 2009, Malacca ; 2009 , Pages 563-568 ; 9780769538792 (ISBN) ; Beigy, H ; Sharif University of Technology
								
								
					2009
				
							
				
		
							Abstract
				
					
			
		
										
				Multi-agent systems (MAS) try to formulate dynamic world which surround human being in every aspect of his life. One of the important challenges encountered in multiagent systems is the credit assignment problem, simply means distributing the result of the work of a group of agents, such that every agent will have the capability of individual learning. This paper presents the result of a solution suggested for multi-agent credit assignment problem. With the help of observing history of credit assignment in the environment, we will understand what actions are reward-deserving. Results are reported on a multi agent domain, addition agents. © 2009 IEEE  
				
				
				
					A Study on Credit Assignment among Reinforcement Learning Agents
, M.Sc. Thesis Sharif University of Technology ; Beigy, Hamid (Supervisor)
							Abstract
				
					
		
		
		
		
		
		
										
				Nowadays, multi-agent systems as part of the distributed artificial intelligence play an important role in modeling and solving complex industrial and commercial problems. They have distinguishing characteristics such as distributiveness (spatial, temporal, semantic, or functional distribution), robustness, parallel processing, etc. One of the capabilities that can be added to this system is the learning capability. It can help the system to adapt itself to the new environment. This paper proposed a method for the problem of credit assignment in multi-agent domain. Solving the multi-agent credit assignment problem, one can expect individual learning for a single agent in systems of... 
				
					Exploration of Existing Patterns in Copy Number Variations of Genetic Diseases and Disorders
, Ph.D. Dissertation Sharif University of Technology ; Rabiee, Hamid Reza (Supervisor)
							Abstract
				
					
		
		
		
		
		
		
										
				One of the main sources of genetic variations are structural variations, including the widespread Copy Number Variations (CNVs). CNVs include two types, copy of genetic material (duplication) and loss of part of genetic sequence (deletion) and typically range from one kilobase pairs (Kbp) to several megabase pairs (Mbp) in size. Most of the copy number variations are occured in in healthy people; however, these variants can also contribute to numerous diseases through several genetic mechanisms (e.g. change gene dosage through insertions, duplications or deletions). The CNV study can provide greater insight into the etiology of disease phenotypes. Nowadays, with the huge amount of investment... 
				
					DeepGenePrior: A deep learning model for prioritizing genes affected by copy number variants
, Article PLoS Computational Biology ; Volume 19, Issue 7 July , 2023 ; 1553734X (ISSN) ; Rabiee, H. R ; Alinejad Rokny, H ; Sharif University of Technology
								
					Public Library of Science 
				
								
								
					2023
				
							
				
		
							Abstract
				
					
			
		
										
				The genetic etiology of brain disorders is highly heterogeneous, characterized by abnormalities in the development of the central nervous system that lead to diminished physical or intellectual capabilities. The process of determining which gene drives disease, known as “gene prioritization,” is not entirely understood. Genome-wide searches for gene-disease associations are still underdeveloped due to reliance on previous discoveries and evidence sources with false positive or negative relations. This paper introduces DeepGenePrior, a model based on deep neural networks that prioritizes candidate genes in genetic diseases. Using the well-studied Variational AutoEncoder (VAE), we developed a... 
				
				
				
					Mesoporous silica nanoparticles (MCM-41) coated PEGylated chitosan as a pH-Responsive nanocarrier for triggered release of erythromycin [electronic resource]
, Article International Journal of Polymeric Materials and Polymeric Biomaterials ; 2014, Volume 63, Issue 13, Pages 692-697 ; Mazaheri Tehrani, Zahra ; Sharif University of Technology
							Abstract
				
					
			
		
										
				A pH-responsive drug delivery system based on core shell structure of mesoporous silica nanoparticle (MSN) and chitosan-PEG copolymer was prepared and characterized by Fourier transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), scanning electron microscope (SEM), and high-resolution transmission microscope (HR-TEM) techniques. In order to improve compatibility MSN and drug, mesoporous nanosilica was modified by 3-aminopropyl triethoxysilane. The release of erythromycin (a macrolide antibiotic) as a model drug was investigated in two pHs, 7.4 and 5.5  
				
				
				
					Theoretical and Computational Investigation of Quantum Plasmonic Properties of Nanocluster Dimers
, M.Sc. Thesis Sharif University of Technology ; Jamshidi, Zahra (Supervisor)
							Abstract
				
					
		
		
		
		
		
		
										
				In today's era, metal nanoparticles play an important role in technologies emerging from different sciences, such as chemistry, physics, optics, material science, due to their unique characteristics. In the development of nanooptics science, it can be said that metal nanoparticles play an important role. The ability of conductive electrons collective oscillation causes surface charge density fluctuations in nanoparticles, this phenomenon is known as surface plasmons. Surface plasmons are surprisingly coupled with light and cause the significant increase in the intensity of optical fields induced in nanoparticles. Therefore, with the presence of localized surface plasmons or plasmon... 
				
					Theoretical Investigation of Ab-initio MD Approach to Increase the Efficiency and Accuracy of VCD Spectrum Calculation
, M.Sc. Thesis Sharif University of Technology ; Jamshidi, Zahra (Supervisor)
							Abstract
				
					
		
		
		
		
		
		
										
				Understanding of the Molecules is the main purpose of the chemistry. Ab-initio molecular dynamics (AIMD) as a branch of the computational chemistry, tries to give us a deep comprehension of the molecule, and its chemical, physical and optical activities. This comprehension, relies on the accuracy of quantum mechanics, in addition to the speed of the classical mechanics. The mixing of the quantum mechanics and the classical mechanics could simulate activities of the atoms in the time-domain, provided the mixing is done with precaution. This, in turn, helps us to forecast the response of a molecule in different situations, and also translating the macroscopic phenomena in a nanoscopic... 
				
					Investigation of Plasmonic Excitation in Carbonic Nanostructures Within Near-IR
, M.Sc. Thesis Sharif University of Technology ; Jamshidi, Zahra (Supervisor)
							Abstract
				
					
		
		
		
		
		
		
										
				To date, the plasmonic properties of many metallic and semi-conducting materials have been investigated and used in various industries. One of the plasmonic material categories that have always been considered is polycyclic aromatic hydrocarbon or PAH, whose plasmonic resonance energy depends on the charge state of the molecule. In this regard, it is easy to change the plasmonic resonance energy via changing the induced charge, which is a unique feature of the mentioned materials. In addition, plasmonic structures with excitations in the infrared region are able to enhance the vibration intensity of absorbed molecules by increasing the electric field around themselves. Therefore, they have... 
				
					Using Nonlinear Effects of Light for Optical Signal Processing
, M.Sc. Thesis Sharif University of Technology ; Kavehvash, Zahra (Supervisor)
							Abstract
				
					
		
		
		
		
		
		
										
				Ultrafast signal processing in time-domain with high resolution and reconfigura-bility is a challenging task. This paper, for the first time, introduces a time-varying metasurface consisting of graphene microribbon array for implementing time-lens in the terahertz domain. Given that the surface conductivity of graphene is proportional to the Fermi energy level in the THz regime, it is possible to change the phase property of the incident electromagnetic pulse by changing the Fermi level while the Fermi level itself is a function of voltage. Upon this fact, a quadratic temporal phase modulator, namely time-lens has been realized. This phase modulation is applied to the impinging signal in the... 
				
					Using Simulation-Optimization Approach for Fire Station Location and Vehicle Assignment Problem: a Case Study in Tehran, Iran
, M.Sc. Thesis Sharif University of Technology ; Amini, Zahra (Supervisor)
							Abstract
				
					
		
		
		
		
		
		
										
				In this research, the problem of locating fire stations and allocating equipment has been studied and a simulation-optimization approach has been presented to solve the problem. The mathematical models of this research were developed based on the idea of the randomness of the covered demand and the maximum expected coverage model. In these models, the issue of non-availability of equipment to cover accidents, the random nature of accidents, various fire incidents and the equipment needed to cover them are considered. Two mathematical models with deterministic and non-deterministic approach with different scenarios for demand are proposed. The non-deterministic model is developed with the aim... 
				
					Introducing An Integrated Framework For Solving The Fleet Planning Problem Using A Simulation-Optimization Approach
, M.Sc. Thesis Sharif University of Technology ; Amini, Zahra (Supervisor)
							Abstract
				
					
		
		
		
		
		
		
										
				One of the main concerns of industrial companies’ managers is providing an efficient logistics system. To achieve an efficient logistics system, the fleet planning problem is studied by many researchers in recent years. This problem consists of multiple sub-problems at three levels: operational, tactical, and strategic. These sub-problems are closely related to each other and need to be studied and addressed in an integrated manner. In this research, an attempt is made to provide an integrated framework to solve the vehicle routing problem (operational), outsourcing problem (tactical), and fleet composition problem (strategic). These problems have various uncertainties, including customer... 
				
					Analytical Modelling and Optimization of Disk Type, Slot Less Resolver
, M.Sc. Thesis Sharif University of Technology ; Nasiri Gheidari, Zahra (Supervisor)
							Abstract
				
					
		
		
		
		
		
		
										
				Resolvers, due to their robust structure, are widely used in automation systems. Among the types of resolvers, the accuracy of the Wound Rotor (WR) resolver in the occurrence of common mechanical errors is higher than other types of resolvers. therefore, in this thesis, an AFWRR is studied to improve the performance. Increasing the number of poles in WR resolvers is a good solution for increasing the accuracy of these electromagnetic position sensors. However, high-speed WR resolvers due to employing fractional slot windings suffer from rich sub-harmonics in the induced voltages. A common solution for suppressing the undesirable sub-harmonics is using multi-layer winding with appropriate... 
				
					A Survey on Searchable Symmetric Encryption Schemes
, M.Sc. Thesis Sharif University of Technology ; Khazaei, Shahram (Supervisor)
							Abstract
				
					
		
		
		
		
		
		
										
				Using “Searchable Encryption” enables us to encrypt the data, while preserving the possibility of running search queries. One of the most important applications of the mentioned is in Cloud Storage. As users do not trust the Cloud space, they are not inclined to store their data on the Could. The solution to this problem is of course, Cryptography. However, ordinary Cryptography methods, eliminate the data’s searchability. Hence, we need encryption schemes that code the data while retaining their searchability. So far, various schemes has been proposed that differ in their performance, security level, and usage. In this thesis, we aim to discuss and analyze these methods  
				
					Time Domain Optical Signal Processing Based on the Duality Between Dispersion and Diffraction
, M.Sc. Thesis Sharif University of Technology ; Kavehvash, Zahra (Supervisor)
							Abstract
				
					
		
		
		
		
		
		
										
				In the last decades, due to the growing demand of transferring information with high transmission rates, the complexity and development of telecommunication and optical systems is remarkable. Researchers around the world attempt to explore extraordinary potential of light to process information. In the mid-19th century, scientists discovered a mathematical symmetry between the spatial and temporal optics fields, which originated from the similarity of equations governing the paraxial diffraction of beams and the dispersion of narrow-band pulses known as space– time duality in scientific texts. This new approach provides more advanced and potent methods to temporal processing and... 
				
					Improving the Stability of an Urban Traffic Network with Limited Data by Using Percolation Theory and Dynamic Clustering
, M.Sc. Thesis Sharif University of Technology ; Amini, Zahra (Supervisor)
							Abstract
				
					
		
		
		
		
		
		
										
				One of the most vital aspects of understanding the traffic phenomenon is scrutinizing the traffic transition status, such as the transition from free flow to congestion. The Percolation Theory is a renowned theory focusing on analyzing various network types to detect the critical zones, which are the zones including links that are important to control to improve stability. By calculating the quality indices of network links, the Percolation Theory can simulate the traffic percolation propagation in the network and determine possible critical zones for further analysis. Most studies in this field assume access to data of several traffic parameters for the entire transportation network, such... 
				
					Temporal Depth Imaging Based on Dispersion
, M.Sc. Thesis Sharif University of Technology ; Kavehvash, Zahra (Supervisor)
							Abstract
				
					
		
		
		
		
		
		
										
				In this thesis, the aim is designing an optical temporal imaging system. In recent years, due to many applications, including the receipt of high-rate data by slow receivers and compensation of dispersion in telecommunication systems, researchers have considered the topic of temporal imaging. This field of research is based on dispersion, electro-optical modulators or time lenses and space-time theory. By modeling dispersion properties as a depth dimension and taking ideas from three-dimensional spatial imaging systems we intended to increase the temporal resolution and depth of focus of the structure. We also present a novel technique for multiplexing and demultiplexing telecommunication... 
				
					Traffic Flow Imputation for Urban Roads with Graph Neural Networks
, M.Sc. Thesis Sharif University of Technology ; Amini, Zahra (Supervisor)
							Abstract
				
					
		
		
		
		
		
		
										
				Traffic data plays an essential role in Intelligent Transportation Systems (ITS) and offers numerous advantages, including efficient traffic control and system performance improvement. However, due to the scarcity of data collection systems, missing data in traffic datasets is inevitable. Therefore, traffic data imputation becomes an essential task. Graph Neural Network (GNN) is a type of neural network that operates on graph-structured data and has shown potential in handling traffic network related tasks such as traffic prediction and traffic data imputation. In this paper, we contribute to the body of knowledge with two aspects. First, we focus on traffic data imputation using solely... 
				
					