In this paper we propose a reinforcement learning (RL) algorithm for packet routing in computer networks with emphasis on different traffic conditions. It is shown that routing with an RL approach, considering the tra...
详细信息
In this paper we propose a reinforcement learning (RL) algorithm for packet routing in computer networks with emphasis on different traffic conditions. It is shown that routing with an RL approach, considering the traffic, can result in shorter delivery time and less congestion. A simple, but rational simulation of a computer network has also been tested and the suggested algorithm has been compared with other conventional ones. At the end, it is concluded that the suggested algorithm can perform packet routing efficiently with advantage of considering the dynamics in a real network
A game is a decision making situation in which each player attempts to act in such a way that the game's circumstances get close to what desirable for him. To reach this goal, a player needs to have a suitable est...
详细信息
A game is a decision making situation in which each player attempts to act in such a way that the game's circumstances get close to what desirable for him. To reach this goal, a player needs to have a suitable estimation of the other players' decisions. In this paper, we propose a fuzzy approach by which a player can attain an estimation of the other players' actions and pursue a strategy which maximizes its performance. Finally, the results of applying the proposed approach to the well-known "prisoner's dilemma" problem are brought to show the effectiveness of the method
This paper addresses the design of state feedback H/sub /spl infin//, robust controller that satisfies additional constraints on closed-loop poles location. Desired closed-loop poles location is considered to be a cli...
详细信息
This paper addresses the design of state feedback H/sub /spl infin//, robust controller that satisfies additional constraints on closed-loop poles location. Desired closed-loop poles location is considered to be a clipped sector, corresponding to some performance specifications such as suitable settling time and overshoot. In order to solve the H/sub /spl infin// optimization problem with two Lyapunov constraints, the Lagrange multiplier is used. It is shown that the appropriate controller is characterized by three coupled algebraic Riccati equations. The validity and applicability of this approach are illustrated by two benchmark examples and the results are compared with those of the conventional H/sub /spl infin// control problem and related works.
The shortcoming of the standard genetic algorithm is analysed. an improved genetic algorithm with modified mutation operator and adaptive probabilities of crossover and mutation is proposed. Simulation experiments hav...
详细信息
Over three decades of parallel computing, new computational requirements and systems have steadily evolved, yet parallel software remains notably more difficult relative to its sequential counterpart, especially for f...
详细信息
We develop a path-following algorithm for redesign of tracking feedback laws to reduce the control effort. Our algorithm provides a tradeoff between the control effort and the dynamic performance along the path, while...
详细信息
We develop a path-following algorithm for redesign of tracking feedback laws to reduce the control effort. Our algorithm provides a tradeoff between the control effort and the dynamic performance along the path, while maintaining the desired convergence to the path. It is applicable to feedback linearizable systems with stable zero dynamics. We illustrate it on a realistic hovercraft model, and compare the resulting control effort with control efforts of other path-following and tracking algorithms.
Active Queue Management (AQM) applies a suitable control policy upon detecting congestion in networks. In this paper, an adaptive Proportional-Integral (PI) controller based on Artificial Neural Networks (ANN) is appl...
详细信息
Active Queue Management (AQM) applies a suitable control policy upon detecting congestion in networks. In this paper, an adaptive Proportional-Integral (PI) controller based on Artificial Neural Networks (ANN) is applied to AQM for the objective of congestion avoidance and control in middle nodes. The proposed controller is simple and can be easily implemented in high-speed routers. Neural Network PI (NNPI) dynamically adapts its parameters with respect to changes in the system. It is anticipated that this results in better response compared to linear controllers due to the nonlinear nature of NNPI. We simulated our method in ns2 and compared its performance with the conventional PI controller. The simulation results show NNPI yields better performance.
The classification of protein structures is essential for their function determination in bioinformatics. The success of the protein structure classification depends on two factors: the computational methods used and ...
详细信息
Robust nonlinear controller design with constraint on the poles’ location of the linear part of closed-loop system is proposed. The design method is based on the integrator backstepping procedure and linear constrain...
详细信息
Robust nonlinear controller design with constraint on the poles’ location of the linear part of closed-loop system is proposed. The design method is based on the integrator backstepping procedure and linear constrained H ∞ for nonlinear strict-feedback systems with disturbance also in strict-feedback form. The resulted closed-loop system will be globally stable, while both local robustness and desired α- stability are achieved. An analytic example is used to compare the performance of the proposed methodology with that of the locally optimal backstepping design with no closed-loop poles constraint.
Although structural constraints such as model order and time delay have been incorporated in the continuous time system identification since its origin, the constraints on the estimated model parameters were rarely en...
详细信息
暂无评论