Abstract Data Type (ADT)
In computing, particularly within the realms of software engineering and Artificial Intelligence/Machine Learning, an Abstract Data Type (ADT) is a conceptual framework for organizing and manipulating data. It defines a data type purely by its behavior as observed from the outside, without any reference to its implementation. This definition includes the type of data it can hold, the operations that can be performed on the data, and the rules for these operations.
ADTs provide a way to encapsulate data and its associated operations, enabling developers to focus on the high-level design and functionality of their systems without being bogged down by the underlying complexities of data representation and manipulation.
A classic example of an ADT in AI/ML is a Queue, which is an ordered collection of elements where additions are made at one end (the "rear") and removals from the other end (the "front"). The Queue ADT is defined by operations such as enqueue (adding an element to the rear), dequeue (removing an element from the front), and isEmpty (checking if the queue is empty), among others.
The specific implementation of a Queue (using an array, linked list, etc.) is hidden from the user, who interacts with it only through its defined operations. In AI/ML applications, Queues can be crucial for managing tasks in algorithms, handling data streams, or scheduling processes in simulations, where the focus is on the abstract behavior of task handling rather than the details of how tasks are stored and retrieved.