Sharif Digital Repository

Emotions are the subject of study in many research areas, including psychology, physiology and artificial intelligence. However, there is not yet a general computational definition for emotions and many of the related works in artificial intelligence are based on uncertain assumptions about the origin, features, and applications of emotions. Therefore, we direct our studies toward achieving a better understanding of emotions and generating a computational model that could be a base for further research in the field. As a first step, we present the results of our study into the possible role of emotions in mental resource management. To do so, we will introduce a model of emotions based on... 

In the modern world, electronic communications play a significant role in national and international electronic transactions. This issue has forced all legal systems to face up to many emerging legal problems in the context of electronic communications, such as the legal status of electronic agents in contracting electronically. Regarding the legal validity of e-contracts made through interactive websites, the legal status of electronic agents which play an important role in this process is questionable to see whether they are akin to real agents in the physical world or they are only a mere tool of communication. The current article tries to analyse this question by criticising a number of... 

One of the most important issues discussed in multi-agent systems, is communication between agents. Usually, a predefined communication protocol is used, but predefining a protocol between agents causes some problems; for example it is possible that agents recognize a subject that is not defined in their protocol so they can't express anything about it. In this paper we propose a new method for evolution of a communication protocol between intelligent agents by using natural selection mechanism. Experimental results will be discussed in detail. © 2006 IEEE  

One of the most important issues that be discussed in multi-agent systems, is the communication between agents. In existing applications usually a communication protocol defined between agents. But defining a protocol between agents cause some problems; for example it is possible that agents recognize a subject, but because it is not defined in their protocol, they can't express any thing about that. In this paper we propose a new method for evolution of a communication protocol between intelligent agents, after that the experimental results will be discussed and at the end of the paper future works and conclusion. Copyright - World Automation Congress (WAC) 2006  

In ubiquitous computing environments, many devices and agents interoperate with each other and use services provided by others. But the problem is that there may be requests that can not be fulfilled by available services. A solution to this problem is to use service brokers that compose existing services and create new value added services that can fulfill the clients' requests. In this paper, we present an architecture for a context-aware service broker that not only is able to compose services for responding to new requests, but also considers the context of its clients for providing customized and personalized outputs and behaviors. © 2006 IEEE  

Zamin artificial life model is designed to be a general purpose environment for researches on evolution of learning methods, living strategies and complex behaviors and is used in several studies thus far. As a main target for Zamin's design has been its expandability and ease of problem definition, a new agent based structure for this artificial world is introduced in this paper, which is believed to be much easier to use and extend. In this new model, all control and world running processes are done by agents. Therefore, any change in world processes does not require recoding the main engine and can be done just by altering the behavior of one or some agents. To have an easier interface... 

In Particle Swarm Optimization (PSO) algorithm, although taking an active role to guide particles moving toward optimal solution, the most-fit candidate does not have a guide itself and only moves along its velocity vector in every iteration. This may yield a noticeable number of agents converge into local optima if the guide (i.e. the most fit candidate) agent cannot explore the best solution. In this paper, an attempt is made to get the advantage of the Ant Colony Optimization (ACO) methodology to assist the PSO algorithm for choosing a proper guide for each particle. This will strengthen the PSO abilities for not getting involved in local optima. As a result, we present a promising new... 

There are many practical situations where it is desirable or even required to achieve stable convergence in the finite-time domain. In this paper, a simple distributed continuous-time protocol is introduced that guarantees finite-time consensus in networks of autonomous agents. Protocol convergence in weighted directed/undirected and fixed/switching networks is explored based on a Lyapunov analysis. The stability of the system and the solvability of the consensus algorithm are proved for network topologies that contain a spanning tree frequently enough over contiguous time intervals. The decision value for different topologies and for multi-rate integrator agents is investigated, and a novel... 

This paper presents a multi agent system which can help type 2 diabetic patients. Because of diabetes nature, medical care and lifestyle can both prevent the complications of this illness, so self-managing is very crucial for these patients. Therefore, each effective factor of controlling diabetes and increasing patients' knowledge including: suitable diet and monitoring blood glucose level, is assigned to be an agent which works independently whilst coordinates and cooperates with other agents. The proposed architecture of this multi agent system organizes all the various agents of this system in a way that not only each of them can accomplish their responsibility, but also they can have... 

The deployment of multi-agent systems in presence of obstacle deals with autonomous motion of agents toward a specified target by sensing each other and boundaries of obstacles. In this paper, asynchronous, scalable, distributed algorithm is used to deploy agents. Boundaries of obstacles are modeled by virtual agents. Algorithm was implemented by solving continuous n-median problem called generalized Fermat-Weber problem. It is shown that deployment is performed when position of real agents are the geometric median of their Voronoi cells. Simulation results show the validity of the proposed algorithm very well  

This paper investigates a new algorithm for flocking of multi-Agent systems with virtual leader. In this algorithm, unlike the existing algorithms, receiving of information by agents are not continuous and it is assumed that each agents receives information of neighbors and virtual leader as sampled data in fixed time intervals. A sufficient condition on sampling period is derived to guarantee the velocity convergence of agents to that of virtual leader, preserve network connectivity, and ensure collision avoidance. Finally, a numerical simulation is provided to illustrate the theoretical results. © 2017 IEEE  

Traditional learning algorithms cannot perform well in scenarios where training data (source domain data) that are used to learn the model have a different distribution with test data (target domain data). The domain adaptation that intends to compensate this problem is an important capability for an intelligent agent. This paper presents a domain adaptation method which learns to adapt the data distribution of the source domain to that of the target domain where no labeled data of the target domain is available (and just unlabeled data are available for the target domain). Our method jointly learns a low dimensional representation space and an adaptive classifier. In fact, we try to find a... 

These days, considering the importance of reliability in industries, utilities’ role for preparing high levels of reliability becomes more important. This can be done by adding numbers of switches and Tie switches which impose high expenses to system. These expenditures should be provided by customers. Level of reliability in different points of network is different. So customers which pay more, receive higher level of reliability. If a customer raises its payment, utility change the location of switches in order to raise level of reliability of that customer. all customers change their payment and then utility fixes the switches at a point that all customers reach their favorable... 

In this paper, an adaptive control scheme for multi-agent formation control is proposed. This control method is based on artificial potential functions integrated with adaptive fuzzy sliding mode control technique. We consider fully actuated mobile agents with completely unknown dynamics. An adaptive fuzzy logic system is used to approximate the unknown system dynamics. Sliding Mode Control (SMC) theory is used to force agents' motion to obey the dynamics defined by the simple inter-agent artificial potential functions. Stability proof is given using Lyapunov functions, which shows the robustness of controller with respect to disturbances and system uncertainties. Simulation results are... 

To address sustainability challenges appeared in today's power grids, it is essential for emerging demand control paradigm to be adapted more to the lifestyle of the customers. In this paper, due to the ever-growing interconnectivity of the grids, a distributed Commodity Market (CM) framework is proposed in which intelligent agents embedded inside of customers want to maximize their preferred welfare through real-time demand of power from an energy market. Since there is not a comprehensive model for the grids, utilizing Reinforcement Learning (RL) proves that the global optimal performance is achieved in the Nash Equilibrium (NE) of the proposed framework. This solution not only maximizes... 

The quantification of carbon dioxide (CO2) dissolution in oil is crucial in predicting the potential and long-term behavior of CO2 in reservoir during secondary and tertiary oil recovery. Accurate predicting carbon dioxide molecular diffusion coefficient is a key parameter during carbon dioxide injection into oil reservoirs. In this study a new model based on adaptive neuro-fuzzy inference systems (ANFIS) is designed and developed for accurate prediction of carbon dioxide diffusivity in oils at elevated temperature and pressures. Particle Swarm Optimization (PSO) as population based stochastic search algorithms was applied to obtain the optimal ANFIS model parameters. Furthermore, a simple...