Abstract
The type of cognitive system (CS) studied here has four basic parts: (1) a set of interacting elementary productions, called classifiers, (2) a performance algorithm that directs the action of the system in the environment, (3) a simple learning algorithm that keeps a record of each classifier's success in bringing about rewards, and (4) a more complex learning algorithm, called the genetic algorithm, that modifies the set of classifiers so that variants of good classifiers persist and new, potentially better ones are created in a provably efficient manner.
Index Terms
- Cognitive systems based on adaptive algorithms
Recommendations
Matrix-Based Channel Hopping Algorithms for Cognitive Radio Networks
Cognitive radio networks (CRNs) have emerged as a critical technique for solving spectrum shortage problems and enhancing the utilization of licensed channels. To prevent interference with the co-locate incumbent networks, before data transmission, nodes ...
Fully distributed algorithms for blind rendezvous in cognitive radio networks
MobiHoc '14: Proceedings of the 15th ACM international symposium on Mobile ad hoc networking and computingRendezvous process is the cornerstone to construct Cognitive Radio Networks (CRNs), through which a secondary user can establish a link for communication with its neighbor on a common channel. Although many blind rendezvous algorithms have been proposed ...
Ring-Walk Based Channel-Hopping Algorithms with Guaranteed Rendezvous for Cognitive Radio Networks
GREENCOM-CPSCOM '10: Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social ComputingRendezvous is a fundamental and essential operation for users of cognitive radio networks (CRNs) to meet and establish a link on a common channel, so that information exchange and data communication can be carried on. This work addresses the problem of ...
Comments