Genetic Programming (GP) is the automated learning of computer programs. Basically a search process, it is capable of solving complex problems by evolving populations of computer programs, using Darwinian evolution and Mendelian genetics as inspiration. GPLAB is a Genetic Programming toolbox for MATLAB. Besides most of the traditional functionalities used in GP, it also implements two additional features: (1) a method for automatically adapting the genetic operator probabilities in runtime, allowing the use of the toolbox as a test bench for new genetic operators; (2) several of the best state-of-the-art techniques for controlling the well known bloat problem, including some that result in automatic resizing of the population in runtime to save computational resources. Combining a highly modular and adaptable structure with the concern for automatic setting of most parameters, GPLAB suits all kinds of users, from the layman who wants to use it as a "black box", to the advanced researcher who intends to build and test new functionalities. The toolbox and its documentation are freely available for download at http://gplab.sourceforge.net. The latest version ensures minimal compatibility with Octave.