The Belief-Desire-Intention (BDI) model is a popular approach to design flexible agents. The key ingredient of BDI model, that contributed to concretize behavioral flexibility, is the inclusion of the practical reasoning. On the other hand, researchers signaled some missing flexibility’s ingredient, in BDI model, essentially the lack of learning. Therefore, an extensive research was conducted in order to extend BDI agents with learning. Although this latter body of research is important, the key contribution of BDI model, i.e., practical reasoning, did not receive a sufficient attention. For instance, for performance reasons, some of the concepts included in the BDI model are neglected by BDI architectures. Neglecting these concepts was criticized by some researchers, as the ability of the agent to reason will be limited, which eventually leads to a more or less flexible reasoning, depending on the concepts explicitly included. The current paper aims to stimulate the researchers to re-explore the concretization of practical reasoning in BDI architectures. Concretely, this paper aims to stimulate a critical review of BDI architectures regarding the flexibility, inherent from the practical reasoning, in the context of single agents, situated in an environment which is not associated with uncertainty. Based on this review, we sketch a new orientation and some suggested improvements for the design of BDI agents. Finally, a simple experiment on a specific case study is carried out to evaluate some suggested improvements, namely the contribution of the agent’s “well-informedness” in the enhancement of the behavioral flexibility.
Selection from perceptual and conceptual representations