In order to handle complex situations, autonomous software agents need multiple components ranging from simple input/output modules to sophisticated AI techniques. Integrating a high number of heterogeneous components is a non-trivial task and this paper proposes the use of a symbolic middleware to handle inter-component interactions. A generalized hyper-graph model is defined, a simple and straightforward representation language is proposed and a pattern matching mechanism is introduced together with a basic performance evaluation. Finally, the paper shows how a flexible symbolic middleware can be built and a few examples are presented.