Radio-frequency identification (RFID) is a wireless communication technology.Radio frequencies can cause interference in a dense RFID system, thus decreasing efficiency. In recent years, many protocols have been proposed to reduce reader collisions based on multiple-access techniques. The main weakness of Time Division Multiple Access (TDMA)-based schemes is the random selection of resources. Additionally, they do not consider the distance between the interfering readers. Therefore, the likelihood of interference in an RFID system will be increased. To address this problem, we propose a new scheme for allocating resources to readers using a learning technique. The proposed scheme takes into account the distance between interfering readers, and these readers acquire the necessary knowledge to select new resources based on the results of the previous selection of neighboring readers using cellular learning automata. This approach leads to reduced interference in an RFID system. The proposed scheme is fully distributed and operates without hardware redundancy. In this scheme, the readers select new resources without exchanging information with each other. The simulation results show that the percentage of kicked readers decreased by more than 20%, and the proposed scheme also provides higher throughput than do state-of-the-art schemes for dense reader environments and leads to further recognition of tags.KEYWORDS cellular learning automata, dense RFID system, interference, reader collision 1 | INTRODUCTION Radio-frequency identification (RFID) is a wireless technology that has attracted a great deal of attention as one of the key elements in the implementation of ubiquitous computing because of features such as flexibility, extensibility, and automatic detection capabilities. Readers and tags are the main components of an RFID system. Wireless readers read the identifier of tags attached to an object and provide access to the object's information by sending the identifier to a backend system. RFID is used in many applications because of its various benefits and features. 1 One of the most important applications of this technology is its use in smart cities. For example, RFID technology is used in the management of smart parking spaces (SPSs). Many SPSs either require expensive equipment or are semiautomated and require some human interaction. However, the use of RFID enables the implementation of a fully automatic SPS management system with much lower costs. The arrival and departure of cars and the management of empty parking spaces can be intelligently controlled using RFID techniques. 2 Another practical application of RFID