Cognitive mapping is a qualitative decision modeling technique developed over twenty years ago by political scientists, which continues to see occasional use in social science and decision-aiding applications. In this paper, I show how cognitive maps can be viewed in the context of more recent formalisms for qualitative decision modeling, and how the latter provide a firm semantic foundation th...

Y.G. Petalas∗1, E.I. Papageorgiou2, K.E. Parsopoulos1, P.P. Groumpos2 and M.N. Vrahatis1 1 Computational Intelligence Laboratory (CI Lab), Department of Mathematics, University of Patras Artificial Intelligence Research Center (UPAIRC), University of Patras, GR-26110 Patras, Hellas 2 Department of Electrical Engineering, Lab. of Automation and Robotics, University of Patras, GR–26500 Patras, He...

Cognitive maps refer to mental representations of maps or environments, as revealed in a variety of tasks. The simplest model of cognitive maps is that they are random degradations of real ones. Research using distance judgments, direction judgments, map recognition, map construction, and other information from memory for maps or environments suggests that distortions, rather than being random,...

Fuzzy Cognitive Maps (FCMs) have been proposed to represent causal reasoning by using numeric processing. They graphically represent uncertain causal reasoning. In the resonant states, there emerges a limit cycle or a hidden pattern, which is a FCM inference. However, there are some shortcomings concerned with knowledge representation in the conventional FCMs. In this paper, we propose Extended...

We describe a computational model of spatial navigation based on experimental studies conducted with human participants. The model builds and uses a hierarchical cognitive map of a large environment. Computer simulations show that the model correctly describes experimental results including hierarchical organization of space and distance estimation. Furthermore, the model predicts that reaction...

The information abstracted by humans and quite complex processes, are usually imprecise or approximate. The adopted modelling strategy is usually imprecise in nature, with no or partial knowledge of the problem, and generally expressed in linguistic terms. Thus, the use of Fuzzy Logic can help solving the ambiguities and vagueness usually faced in this kind of problems. Soft computing technique...