In this paper, we present a directly applicable scheme for electricity consumption shifting and effective demand curve flattening. The scheme can employ the services of either individual or cooperating consumer agents alike. Agents participating in the scheme, however, are motivated to form cooperatives, in order to reduce their electricity bills via lower group prices granted for sizable consu...

The goal of this paper is to improve the performance of the well known Q learning algorithm, the robust technique of Machine learning to facilitate path planning in an environment. Until this time the Q learning algorithms like Classical Q learning(CQL)algorithm and Improved Q learning (IQL) algorithm deal with an environment without obstacles, while in a real environment an agent has to face o...

Recently, reinforcement learning has been applied to cryptocurrencies make profitable trades. However, cryptocurrency trading is a very challenging task due the volatility of market, especially during bearish periods. In addressing this problem, existing literature employs single-agent techniques such as deep Q-network (DQN), advantage actor-critic (A2C), and proximal policy optimization (PPO),...

Reinforcement learning is an adaptive process in which an animal utilizes its previous experience to improve the outcomes of future choices. Computational theories of reinforcement learning play a central role in the newly emerging areas of neuroeconomics and decision neuroscience. In this framework, actions are chosen according to their value functions, which describe how much future reward is...

in this paper, we consider a cooperative cognitive radio network in which there is an ofdm primary link and multiple single carrier secondary links.the primary link is required to maintain its secrecy rate above a predefined threshold. if the secrecy rate requirement is not satisfied, the secondary system help primary link to maintain its secrecy rate requirement. in doing so, the secondary trans...

Trust management is an important security approach for the successful implementation of Vehicular Ad Hoc Networks (VANETs). models evaluate messages to assign reward or punishment. This can be used influence a driver’s future behaviour. In author’s previous work, sender-side based trust framework developed which avoids receiver evaluation messages. However, this does not guarantee that trusted ...

Competition between a complex system's constituents and a corresponding reward mechanism based on it have profound influence on the functioning, stability, and evolution of the system. But determining the dominance hierarchy or ranking among the constituent parts from the strongest to the weakest--essential in determining reward and penalty--is frequently an ambiguous task due to the incomplete...

In this paper, mesh-free element free Galerkin (EFG) method is extended to solve two-dimensional potential flow problems. Two ideal fluid flow problems (i.e. flow over a rigid cylinder and flow over a sphere) have been formulated using variational approach. Penalty and Lagrange multiplier techniques have been utilized for the enforcement of essential boundary conditions. Four point Gauss quadra...