Computational intelligence based architecture for cognitive agents

AbstractWe discuss some limitations of reflexive agents to motivate the need to develop cognitive agents and propose a hierarchical, layered, architecture for cognitive agents. Our examples often involve the discussion of cognitive agents in highway traffic models. A cognitive agent is an agent capable of performing cognitive acts, i.e. a sequence of the following activities: “Perceiving” information in the environment and provided by other agents, “Reasoning” about this information using existing knowledge, “Judging” the obtained information using existing knowledge, “Responding” to other cognitive agents or to the external environment, as it may be required, and “Learning”, i.e. changing (and, hopefully augmenting) the existing knowledge if the newly acquired information allows it. We describe how computational intelligence techniques (e.g., fuzzy logic, neural networks, genetic algorithms, etc) allow mimicking to a certain extent the cognitive acts performed by human beings. The order with which the cognitive actions take place is important and so is the order with which the various computational intelligence techniques are applied. We believe that a hierarchical layered model should be defined for the generic cognitive agents in a style akin to the hierarchical OSI 7 layer model used in data communication. We outline in broad sense such a reference model