In this thesis, we deal with blackboard system performance issues. We show that blackboard system performance can be improved by using parallel processing strategies and a novel blackboard architecture. We study traditional blackboard architectures using a novel performance framework. This is a useful tool for directing system optimization efforts. We present the analysis of four blackboard systems present in the literature. Besides localised optimization efforts, one of the most promising approaches for improving blackboard system performance is the use of parallel processing techniques. However, traditional blackboard architectures present both data and control contention when implemented in parallel. In this thesis we present a novel blackboard architecture, the Active Blackboard Architecture (ABB). We base ABB on a new variation of the traditional "Blackboard and Experts" metaphor, called "Blackboard, Experts and Desks". This new metaphor introduces a new element, the desks, used by the experts to perform their work. The ABB architecture provides an active blackboard, capable of processing on its own, and a novel decentralised control model. This control model avoids control contention and bottlenecks. In this thesis, we formally describe this architecture using the Z specification language. We also present an implementation, the ABB parallel prototype, and we evaluate its performance using the EPCC Meiko Computing Surface, a multi-transputer distributed memory parallel machine. The ABB Parallel prototype is an object oriented implementation of the ABB model that overcomes both data and control bottlenecks by having a distributed blackboard and using the ABB control model. Based on a series of experiments, we show that the new architecture allows to achieve much greater effective parallelism in a blackboard system. We also present some ways in which the system can be tailored to specific application needs, improving in this way its overall performance.