This bachelor's project uses the Spotify API (Application Programming Interface) to implement a new application called SpotBox, a “digital jukebox”. As it is known, the traditional jukebox has disappeared from the market. There are many reasons for this, such as the limitation of storage capacity and the update frequency of music is not timely. This project proposes to apply the digital technology to build a new jukebox system. The idea is to build an application based on Spotify to run in an ordinary computer that could control the incoming of the coins and the selection of the music. This new version of the jukebox, the digital jukebox, would be deployed in pubs and discos.The development utilized C# as the programming language and the operation system is Microsoft Windows.The method of the project has 3 steps. The first step is the application requirements‟ analysis. This step identifies and analyses the requirements of the application to work as a digital jukebox and the additional functions based on the Spotify.The second step is the study about the Spotify API (Application Programming Interface). This is necessary step to verify what is possible to implement from the identified requirements.Finally, the work was concluded by implementing the required functionalities, as well as a enhancing the graphical interface. The graphical interface combined with these functionalities composes an application prototype.As for the main result, the application was fully developed with the minimum required functionality and interface. Secondary results can be named as the report of the possibilities that allowed by the Spotfy API together with the complete requirement analysis of the functionalities that were outside the scope of the intended prototype implementation.

M.Sc. (Computer Science) / Artificial Intelligence has been an increasing focus of study over the past years. Agent technology has emerged as being the preferred model for simulating intelligence [Jen00a]. Focus is now turning to inter-agent communication [Jen00b] and agents that can adapt to changes in their environment. Digital music has been gaining in popularity over the past few years. Devices such as Apple’s iPod have sold millions. These devices have the capability of holding thousands of songs. Managing such a device and selecting a list of songs to play from so many can be a difficult task. This dissertation expands on agent types by creating a new agent type known as the Modifiable Agent. The Modifiable Agent type defines agents which have the ability to modify their intelligence depending on what data they need to analyse. This allows an agent to, for example, change from being a goal based to a learning based agent, or allows an agent to modify the way in which it processes data. Digital music is a growing field with devices such as the Apple iPod revolutionising the industry. These devices can store large amounts of songs and as such, make it very difficult to navigate as they usually don’t include devices such as a mouse or keyboard. Therefore, creating a play list of songs can be a tiresome process which can lead to the user playing the same songs over and over. The goal of the dissertation is to provide research into methods of automatically creating a play list from a user selected song, i.e. once a user selects a song, a list of similar music is automatically generated and added to the user’s playlist. This simplifies the task of selecting music and adds diversity to the songs which the user listens to. The dissertation introduces intelligent music selection, or selecting a play list of songs depending on music classification techniques and past human interaction.