A representation of partial spatial knowledge: a cognitive map approach for evacuation simulations

This paper presents a method for the representation and reasoning of spatial knowledge. Spatial knowledge is important to decision making in many transportation applications that involve human judgment and understanding of the spatial nature of the transportation infrastructure. Unfortunately, conventional Knowledge-Based Expert Systems (KBESs) do not have a robust spatial inference engine to construct spatial knowledge and deduce solutions. The method discussed in the paper integrated a KBES with geographic information system (GIS) functions using Transmission Control Protocol/Internet Protocol and Remote Procedure Calling technologies. A software system (called IntelliGIS) implementing the method has been developed. As a case study, a KBES-based pavement management system was developed using the IntelliGIS. The case study demonstrated how IntelliGIS represents and reasons about spatial knowledge and how it provides graphical display capabilities for representing spatial information and derived solutions.

A series of experiments demonstrated that a congenitally blind 2 1/2-year-old child-as well as sighted but blindfolded children and adults-can determine the appropriate path between two objects after traveling to each of those objects from a third object. This task requires that the child detect the distances and the angular relationship of the familiar paths and that she derive therefrom the angle of the new path. Our research indicates that the locomotion of the young blind child is guided by knowledge of the Euclidean properties of a spatial layout and by principles for making inferences based on those properties.

The objective of the article is to show the algorithm of international relations geoinformation mapping. During the mapping we can mine unknown or hidden knowledge which can be understood from the spatial database and improve the ability of interpreting data. The algorithm of mapping can be divided into five phases described as follows: investigation of potential map user’s demands, spatial data analysis and selection (accuracy, consistency, fullness); scale, map projections and map composition choice (main meridian, map frame, map distortions), spatial data preprocessing (metadata description, data normalization, data generalization, data quality control, error detection, anomalies, duplication and noise detection, correction of errors, data deduplication), data mining (creation of classifications, cluster and factor analysis, decision trees, neural networks, self-organizing maps, association rules, quality assessment), map creation, knowledge representation and evaluation. The article arranges experience of international relations geoinformation mapping. The international relations maps of Ukraine potential users (state and region management, educational, cultural, advocacy, international marketing and advertising, media business), subjects (substance, energy and information flows) and indicators arrays are proposed. Main subjects of maps can be described as follows: military-political, economicpolitical, socio-political and ideological relations; migrations and refugees, international tourism, export and import of goods and services, information flows (flows of culture elements, artifacts and tangible cultural monuments, scientific knowledge, ideas, technologies, traditions, beliefs, ideology, etc.), transport and business infrastructure. The requirements for spatial data sources for international relations geoinformation mapping are defined. The algorithm of international relations static and interactive maps creation and analysis are founded. The flow chart of Ukraine international relations geoinformation mapping algorithm is presented.

Environmental Psychology: Overview

Spatial memory and reasoning rely heavily on allocentric (often map-like) representations of spatial knowledge. While research has documented many ways in which spatial information can be represented in allocentric form, less is known about how such representations are constructed. For example: Are the very early, pre-attentive parts of the process hard-wired, or can they be altered by experience? We addressed this issue by presenting sub-saccadic (53ms) masked stimuli consisting of a target among one to three reference features. We then shifted the location of the feature array, and asked participants to identify the target's new relative location. Experience altered feature processing even when the display duration was too short to allow attention re-allocation. The results demonstrate the importance of early perceptual processes in the creation of representations of spatial location, and the malleability of those processes based on experience and expectations.

Wormholes in virtual space: From cognitive maps to cognitive graphs

A60 Can Creating Livable and Complete Streets Improve Children’s Spatial Knowledge? A Cognitive Mapping Study of the Influence of Traffic and Safe Routes to School (SR2S) Projects on Schoolchildren in a US Suburban Context

How we think and behave in geographic space is an important topic that researchers from a variety of disciplines have sought to understand. They have been especially interested in analysing what people know about spatial relationships at the geographic scale and how they use this knowledge in everyday spatial behaviour and decision- making. Little attempt has been made, however, to draw together theory and practice from across and within this wide variety of disciplines. In seeking to do this Rob Kitchin and Mark Blades have three aims: to provide a synthesis of knowledge from across the disciplines; to provide a critical appraisal of the field; and to put forward new ideas and theories concerning cognitive mapping whilst outlining a future agenda for research.

Enhancing Apartment Building Design with 3D Knowledge Graphs and Large Language Models: A workflow for automated spatial recognition knowledge representation and natural language interaction in early-stage design

The hippocampus may have a time-limited role in memory, being needed only until information is permanently stored elsewhere, or this region may permanently represent long-term allocentric spatial information or cognitive maps in memory. To test these ideas, we investigated remote spatial memory in K.C., a patient with bilateral hippocampal lesions and amnesia for autobiographical events. In his spatial knowledge, general aspects were preserved, but details were lost, a pattern that resembled his memory loss in other domains. K.C. performed normally on allocentric spatial tests of his neighborhood and the world. He had difficulty, however, in recognizing and identifying non-salient neighborhood landmarks, and in recognizing city locations on world maps. This suggests that the hippocampus is not crucial for maintenance and retrieval of remotely formed spatial representations of major landmarks, routes, distances and directions, but is necessary for specifying location details, regardless of when they were acquired.

Neuropsychological investigations of visual imagery and representations have led to a deeper understanding of the spatial perception, representation and memory. But how each individual perceives object’s geometrical properties and how they differ from person to person, both under event-related memory and normal recollecting memory in the presence or in the absence of direct sensory stimulation is still unclear. Spatial knowledge is diverse, complex, and multi-modal, as are the situations in which it is used. All seem to agree that a cognitive map is a mental representation of an external environment. The image scaling is important in understanding the psychological dysfunctions of patients suffering from spatial cognition problems. The scaling becomes self-evident in art forms, when people are asked to draw image of objects they see actively or from their short or long term memory. In this paper we develop a comprehensive model of this scaling factor and its implications in spatial image representation and memory. We also extend its notion in understanding the perception of objects whose representations are normally not possible (like the perception of universal scales, infinities and parallel lines) but are well comprehended by the human brains. Here we give a scaling factor which is variable depending on the situations for a person based on his visual memory and drawing capabilities. And then extend it to analyse his cognitive strengths, disorders and any imperfections. This model also helps in formalizing the architectural cognitive maps needed to change the scaling factor, depending on the types of visual works one performs.

Locative media utilize actual physical location as an important interaction parameter. Consequently, factors such as the users' spatial abilities and spatial knowledge, usually related to their cognitive maps come into play and may be manifested in the form of map-like representations. This paper extends previous work on the implications of locative media use for spatial perception and cognition by presenting results from a field research that utilized a location-based multi-user communication system in the city of Athens, Greece in order to study the perception of the urban environment and the formulation of spatial cognitive structures as a result of the system's use. The users' spatial representations were assessed by a combination of quantitative and qualitative methods which primarily consisted of questionnaires, focus groups, and sketch mapping, i.e. map-like sketches of the activity area, made by the users themselves after taking part in the activity.

Decentralized self-adaptive systems consist of multiple control loops that adapt some local and system-level global goals of each locally managed system or component in a decentralized setting. As each component works together in a decentralized environment, a control loop cannot take adaptation decisions independently. Therefore, all the control loops need to exchange their adaptation decisions to infer a global knowledge about the system. Decentralized self-adaptation approaches in the literature uses the global knowledge to take decisions that optimize both local and global goals. However, coordinating in such an unbounded manner impairs scalability. This paper proposes a decentralized self-adaptation technique using reinforcement learning that incorporates partial knowledge in order to reduce coordination overhead. The Q-learning algorithm based on Interaction Driven Markov Games is utilized to take adaptation decisions as it enables coordination only when it is beneficial. Rather than using unbounded number of peers, the adaptation control loop coordinates with a single peer control loop. The proposed approach was evaluated on a service-based Tele Assistance System. It was compared to random, independent and multiagent learners that assume global knowledge. It was observed that, in all cases, the proposed approach conformed to both local and global goals while maintaining comparatively lower coordination overhead.

Interest in applications based on distributed ledger technology (DLT) is on the rise, with corporations worldwide shifting from simply exploring DLT’s potential to creating productive business cases. However, despite the existence of numerous DLT applications, developers are still lacking proper tools and instruments for evaluating system behavior (e.g., performance) of their applications on different distributed ledgers before deployment. Since the behavior of such applications is highly dependent on the characteristics of the distributed ledger they are built upon and changing the distributed ledger after deployment of an application is difficult, selecting the wrong ledger can have severe negative consequences. To address the issue, we conducted an extensive literature review to identify and synthesize published modeling and simulation approaches for distributed ledgers. Based on the results, this paper also presents a research agenda to improve modeling of the system behavior of distributed ledgers and to support the development of distributed ledgers and viable DLT applications. In doing so, we facilitate informed decision-making for suitable modeling or simulation approach, which helps application developers to identify a suitable distributed ledger before implementing an application. In addition, our work contributes to science, as we provide a comprehensive overview and analysis of extant simulation and modeling approaches in DLT that accumulates the current state-of-the-art in the rapidly growing DLT field.

Precast and prestressed concrete played a prominent role in meeting the stiff requirements of the new USAA Southeast Regional Office Building and Parking Structure in Tampa, Florida. The seven-story office building and five-level parking structure are separated into two curving volumes facing an existing man-made lake. These volumes unite to form a single south facade characterized by a large-scale grid of punched windows in a horizontally banded exterior wall. The free standing 1600-car parking structure is all-precast, employing a distinctive loadbearing ladder wall system with a pretopped double tee floor system. The authors present the architectural requirements and environmental issues, the structural design considerations and some production/erection highlights of the proiect. A key ingredient, which ensured the success of the project, was the concept of partnering ― the theme of which is carried throughout the article