Papers by Keyword: Multi-Agent System (MAS)

Abstract: The usage of renewable energy systems increases worldwide due to extinction of conventional sources and also the absence of some serious environmental effects such as global warming, ozone layer depletion etc. These renewable power systems are not able to satisfy the load continuously due to seasonal availability of the resources. A Hybrid Power System (HPS) formed with renewable energy sources are a solution to provide power for stand-alone electrical loads. However, the energy management in HPS is quite complex as it relies on a central controller. This paper proposes a distributed Energy Management System (EMS) to control the energy flow in the PV/Wind/Fuel Cell/Battery HPS based on multi-agent system (MAS) technology. With this concept, a HPS is seen as a collection of different elements called agents, collaborates to reach a global coordination to satisfy the demand in the system. The Algorithm of the Multi-Agent System technique for HPS has been implemented using MATLAB/Simulink environment. The results show that the algorithm is effectively working for a HPS to provide power to the load and control power flow between various elements of the system.

Abstract: The learning behaviours of buyers and sellers with the assumption of bounded rationality were studied in the double sealed-bid bargaining mechanism. A multi-agent simulation trading system was constructed to observe the process of equilibrium approach when exist the multiple equilibria. The bidding choices of the agents were modelled by particle swarm optimization (PSO) algorithm. In our proposed model, two populations of buyers and sellers were randomly matched to deal repeatedly until the iteration stop, and each agent would update his bidding strategy in each round by imitating the successful member in his population and by private experience. Results show that the final biddings of the agents in both populations commonly approach a Nash equilibrium which is reasonable for the market principle.

Abstract: In Multi-Agent System, obligations are actions that agents are required to take or some states of affairs which should be maintained, formal modeling and verifying obligation policy which is high-level requirements specifications or communication protocol for constraining agent interaction can enhance the correctness of the system design. Therefore, in this paper a formal framework language for modeling obligation policy is introduced. In this method, the obligations are defined as a special social commitment, the state models of obligation are defined by classifying the obligation. Then we use the policy context and state model to formal the dynamic execution of obligation policy, finally the operational semantics of the framework language is defined as a state transition system which has Kripke semantic structure and it can be as formal foundation for model checking.

Abstract: Applications on Multi-agent system have been widely studied recently. The positioning of Robotic system is to estimate the position and posture and accurate position estimation. FastSLAM is a SLAM algorithm based on particle filtering, which can perform positioning fast and has been widely applied. This paper applied the genetic particle filtering into SLAM problem to optimize the SLAM algorithm. We present the algorithms based on genetic particle filtering which can obviously reduce the number of particles needed in FastSLAM. The experimental results show that the improvement measures can effectively improve the performance of the algorithm, so that it enables them to maintain a reliable positioning.

Abstract: DEC-POMDP(Distributed Partially Observable Markov Decision Process) model is a multi-agent model of collaborative decision-making is important, but due to an alarming number of DEC-POMDP problem state space and great strategy solution space, so DEC-POMDP solution of the problem becomes very difficult. The agent from the initial state to the target state during the interaction with the environment, the system's maximum benefit is often only with some small amount of a higher reward states. This article by searching from the initial belief state to the target state to get a shortest Hamiltonian path, according to the corresponding sequence of actions on the path forward search to get faith belief state space trajectory, and then along the trajectory reverse convictions value function iteration, thus forming the state with the largest gains beliefs trajectory corresponding optimal strategy. In this paper, shortest Hamiltonian path-based value iteration to search the optimal path of faith so as to solve the state Hamiltonian larger DEC-POMDP problem.

Abstract: Transportation simulations are an important part of today’s decision making process for transport infrastructure and management. While proposed changes are getting more and more complex, tools supporting the decision making process are struggling to keep up. Traditional, flow-based traffic assignment tools are limited in the number of different person groups that can be distinguished and do in most cases not offer fully time-dynamic results. Newer technologies like agent-based simulations overcome those problems. This paper presents a novel traffic simulation scheme capable of modeling chaotic motorway traffic. Different from other lane-based or following-based approaches, the proposed approach models traffic as a large navigational problem in an agent based simulation context. In addition, the approach is efficiently able to handle hard cases like overtaking, behavior at turning and aggressive driving behavior. The simulation was demonstrated at real-time rates using MATSim applied to Cairo Ring Road. It has been described as well how MATSim simulation was extended to incorporate aggressive and careless drivers' behavior.

Abstract: E-commerce multi-agent systems have some features of autonomy and commercial transaction that improve rapidly and become a powerful tool for buying and selling products online. While multi-agent systems can break interactions in distributed and heterogeneous environments, malicious behaviors of the agents are a potential hazard in distributed e-commerce applications. Hence, calculating the reliability and reputation of agents play a critical role in determining how interactions occur and who to interact with. The way of calculating the reliability and reputation of each agent should be based on different elements, and there are no standard elements to compute reliability and reputation of each agent in multi-agent environment. This paper analyses some recent proposed methods in calculating reputation and reliability of each agent. The ultimate aim of this study is to define the standard elements which should be considered to calculate the reliability and reputation of agents in e-commerce multi-agent environment.

Abstract: In this paper, we mainly study input-to-state-stability (ISS) for the multi-agent systems with directed graph and the communication noise under switching interaction topologies, using the method of input-to-state-stability, input-to-state-stability -Lyapunov function. We point out the results of [5] is correct, but the proof of its main theorem has a small mistake, we give the proof by quite a different method.

Abstract: This paper researches the corresponding inference-machine, which can adapt to complexity of the net-topology, the diversity of the operation task and the flexibility of operation mode. Multi-agents share information and cooperate to generate the right operation sheets. The system is used in one county power dispatching center.

Abstract: In the paper, we analyze the distributed flocking algorithms with communication noise. Under the Boid model, flocking algorithm with communication noise is easy to diverge. In order to improve the convergence performance of flocking algorithms with communication noise, and overcome the impact brought by communication noise on flocking algorithm, in the paper, a distributed flocking algorithm based on SO-DCT distributed consensus algorithm is proposed. The second-order flocking algorithm under the Boid model is analyzed, and simulations are done. Results show that the second-order distributed flocking algorithm can reach cohesion, and its convergence performance is better than that of the first-order distributed flocking algorithm, moreover, the impact of communication noise on the second-order flocking algorithm is smaller.