Computational trust and reputation models have been recognized as one of the key technologies required to design and implement agent systems. These models manage and aggregate the information needed by agents to efficiently perform partner selection in uncertain situations. For simple applications, a game theoretical approach similar to that used in most models can suffice. However, if we want to undertake problems found in socially complex virtual societies, we need more sophisticated trust and reputation systems, that not only focus on the construction and inference of social evaluations (epistemic decisions), but on the their role in the practical reasoning performed by the agents (pragmatic-strategic decisions) and on communications and dialectical processes (memetic decisions). Most of the current state-of-the-art models struggle with epistemic decisions, on how agents evaluate other agents according to certain criteria. Curiously, pragmatic-strategic and memetic decisions are traditionally left apart, either because they are implicit in the model or because it is too dependent on the domain. This thesis explores this gap, arguing that in complex scenarios where more cognitive approaches are needed, both pragmatic-strategic and memetic decisions are as important as epistemic ones.