Cognitive Agent-Based Life Process Modelling to Predict Social Performance in Workplace Design

DC I/O 2020 ◽  
2020 ◽  
Author(s):  
Patrik Schumacher ◽  
◽  
Tyson Hosmer ◽  
Ziming He ◽  
Sobitha Ravichandran ◽  
...  
Author(s):  
Xuexin Duan

AbstractA new framework, agenda and practice is called for to address the challenges and opportunities architecture must confront in the age of our computationally empowered Post-Fordist network society. This paper introduces the research agenda of ‘agent-based parametric semiology’, and explains the necessity of introducing a new tool, agent-based life-process modelling, as part of the design process, in order to cope with the new complexity and dynamism of architecture’s social functionality. The paper reviews the development of this design research program over the last 10 years. Finally, the paper describes current efforts to move from the illustrative use of life-process modelling to a scientifically grounded quantitative analysis and generative design optimization.


Agents are relatively autonomous computational objects. They can slightly differ in values of their properties, called attributes, and can as well have different number of quite different properties. Agents exchange messages and carry out activities influencing other agents and environment. Agent activities are defined by its own rules that can be static or dynamic. Simulation of various phenomena using agents are called agent-based modelling (ABM). ABM enables observation and investigation of processes that are complicated to be modelled by other modelling means. The purpose of this chapter is to demonstrate the agent-based approach for modelling and analyzing agents-customers flow to shops or service places. Each agent randomly with defined probability decides if the service is to be booked or not. Flow of customers is modelled by another kind of single agent environment. This real-world process modelling by means of agents enables to collect statistics and to compare outcomes with similar analytical results.


Author(s):  
Muaz A Niazi ◽  
Amir Hussain
Keyword(s):  

Author(s):  
Lokesh B. Bhajantri ◽  
Vasudha V. Ayyannavar

In the recent past, some research works are focused on the design and management of ubiquitous networks (UNs) in terms of performance metrics like routing, computation overhead, latency, and security. Nowadays, data synchronization is one of the most challenging tasks in UNs to ensure the data consistency between the nodes or devices and servers. In this work, the authors present an overview of the UNs, including issues and challenges, cognitive agents, synchronization algorithms, and proposed data synchronization model using cognitive agents. This review article classifies some of the data synchronization algorithms into four categories named: synchronization based on the message digest; timestamp based synchronization; synchronization based on scalability performance; and delta synchronization with their relative performance. This article also compares synchronization algorithms against data synchronization in terms of accuracy, efficiency, scalability, consistency, and control overheads. The authors provide the model of cognitive agent-based data synchronization in UNs, which ensures the network performance in terms of reliability, energy efficient, accuracy, scalable, fault tolerant, and QoS based data synchronization algorithms using cognitive agents.


2015 ◽  
Vol 51 ◽  
pp. 463-472 ◽  
Author(s):  
Nataliya Mogles ◽  
Alfonso P. Ramallo-González ◽  
Elizabeth Gabe-Thomas

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