Do animals have cognitive maps?

Drawing on studies of humans, rodents, birds and arthropods, I show that 'cognitive maps' have been used to describe a wide variety of spatial concepts. There are, however, two main definitions. One, sensu Tolman, O'Keefe and Nadel, is that a cognitive map is a powerful memory of landmarks which allows novel short-cutting to occur. The other, sensu Gallistel, is that a cognitive map is any representation of space held by an animal. Other definitions with quite different meanings are also summarised. I argue that no animal has been conclusively shown to have a cognitive map, sensu Tolman, O'Keefe and Nadel, because simpler explanations of the crucial novel short-cutting results are invariably possible. Owing to the repeated inability of experimenters to eliminate these simpler explanations over at least 15 years, and the confusion caused by the numerous contradictory definitions of a cognitive map. I argue that the cognitive map is no longer a useful hypothesis for elucidating the spatial behaviour of animals and that use of the term should be avoided.

A Conceptual Model to Combine Creativity Techniques with Fuzzy Cognitive Maps for Enhanced Knowledge Management

This chapter introduces a conceptual model to combine creativity techniques with fuzzy cognitive maps (FCMs) and aims to support knowledge management methods by improving expert knowledge acquisition and aggregation. The aim of the conceptual model is to represent acquired knowledge in a manner that is as computer-understandable as possible with the intention of developing automated reasoning in the future as part of intelligent information systems. The formal represented knowledge thus may provide businesses with intelligent information integration. To this end, we introduce and evaluate various creativity techniques with a list of attributes to define the most suitable to combine with FCMs. This proposed combination enables enhanced knowledge management through the acquisition and representation of expert knowledge with FCMs. Our evaluation indicates that the creativity technique known as mind mapping is the most suitable technique in our set. Finally, a scenario from stakeholder management demonstrates the combination of mind mapping with FCMs as an integrated system.

Verbalization of Dependencies Between Concepts Built Through Fuzzy Cognitive Maps

The new computing paradigm known as cognitive computing attempts to imitate the human capabilities of learning, problem solving, and considering things in context. To do so, an application (a cognitive system) must learn from its environment (e.g., by interacting with various interfaces). These interfaces can run the gamut from sensors to humans to databases. Accessing data through such interfaces allows the system to conduct cognitive tasks that can support humans in decision-making or problem-solving processes. Cognitive systems can be integrated into various domains (e.g., medicine or insurance). For example, a cognitive system in cities can collect data, can learn from various data sources and can then attempt to connect these sources to provide real time optimizations of subsystems within the city (e.g., the transportation system). In this study, we provide a methodology for integrating a cognitive system that allows data to be verbalized, making the causalities and hypotheses generated from the cognitive system more understandable to humans. We abstract a city subsystem—passenger flow for a taxi company—by applying fuzzy cognitive maps (FCMs). FCMs can be used as a mathematical tool for modeling complex systems built by directed graphs with concepts (e.g., policies, events, and/or domains) as nodes and causalities as edges. As a verbalization technique we introduce the restriction-centered theory of reasoning (RCT). RCT addresses the imprecision inherent in language by introducing restrictions. Using this underlying combinatorial design, our approach can handle large data sets from complex systems and make the output understandable to humans.

Synchronizing Mind Maps with Fuzzy Cognitive Maps for Decision-Finding in Cognitive Cities

Synchronizing mind maps with fuzzy cognitive maps can help to handle complex problems with many involved stakeholders by taking advantage of human creativity. The proposed approach has the capacity to instantiate cognitive cities by including cognitive computing. A use case in the context of decision-finding (concerning a transportation system) is presented to illustrate the approach.

Enhanced Knowledge Management by Synchronizing Mind Maps and Fuzzy Cognitive Maps

This paper presents a conceptual approach to enhance knowledge management by synchronizing mind maps and fuzzy cognitive maps. The use of mind maps allows taking advantage of human creativity, while the application of fuzzy cognitive maps enables to store information expressed in natural language. By applying cognitive computing, it makes possible to gather and extract relevant information out of a data pool. Therefore, this approach is supposed to give a framework that enhances knowledge management. To demonstrate the potential of this framework, a use case concerning the development of a smart city app is presented.

Applying the Fuzzy Analytical Hierarchy Process in Cognitive Cities

This paper introduces a mobile application (app) as the first part of an interactive framework. The framework enhances the inter-action between cities and their citizens, introducing the Fuzzy Analytical Hierarchy Process (FAHP) as a potential information acquisition method to improve existing citizen management en-deavors for cognitive cities. Citizen management is enhanced by advanced visualization using Fuzzy Cognitive Maps (FCM). The presented app takes fuzziness into account in the constant inter-action and continuous development of communication between cities or between certain of their entities (e.g., the tax authority) and their citizens. A transportation use case is implemented for didactical reasons.

Fuzzy knowledge representation in cognitive cities

This paper gives an insight into cognitive computing for smart cities, resulting in cognitive cities. Cognitive cities and cognitive computing research with the underlying concepts of knowledge graphs and fuzzy cognitive maps are presented and supported by existing tools (i.e., IBM Watson and Google Now) and intended tools (meta-app). The paper illustrates FCM as a suiting instrument to represent information/knowledge in a city environment driven by human-technology interaction, enforcing the concept of cognitive cities. A proposed paper prototype combines the findings of the paper and shows the next step in the implementation of the proposed meta-app.

Personal Digital Assistant 2.0 - A Software Prototype for Cognitive Cities

This paper presents a software prototype of a personal digital assistant 2.0. Based on soft computing methods and cognitive computing this mobile application prototype improves calendar and mobility management in cognitive cities. Applying fuzzy cognitive maps and evolutionary algorithms, the prototype represents a next step towards the realization of cognitive cities (i.e., smart cities enhanced with cognition). A user scenario and a test version of the prototype are included for didactical reasons.