Theodore C. Belding’s research while affiliated with Concordia University Ann Arbor and other places

... This is very important: if there is no diversity of opinion, then that group will only think along a converged set of ideas and is vulnerable to unexpected changes in the environment. This is termed as cognitive collapse in the literature [12]. ...

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Analyzing opinion dynamics in online social networks

... (Ku et al. 2015, p. 95) Conflict management competency Process through which individuals manage conflict in an efficient, fair and respectful manner. Subtheme 1b: interpretation of sustainability leadership How key actors interpreted their information Cognitive convergence When individuals think more and more along the same lines (Parunak et al. 2008) Cognitive depletion Exhaustion of cognitive resources via stressors and demands consequently affecting one's ability to think clearly and holistically Theme 2: modifying organizational frames of reference Process through which key actors modified or changed their frames of reference (i.e. belief structures that shape perception and communication) Subtheme 2a: perceptions of goal misalignment ...

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"Can you drink money?": Integrating Organizational Perspective-taking and Organizational Resilience in a Multi-level Systems Framework for Sustainability Leadership

... A " polyagent " is the modeling construct introduced in the agent-based modeling work of Parunak and Brueckner. It is an approach to systems modeling designed to address some limitations of agent-based modeling (Parunak et al., 2007; Brueckner et al., 2009). It consists of two basic elements: the polyagent construct and stigmergic interactions. ...

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A Control Architecture of Complex Systems Based on Multi-agent Models

... Predictive control or model predictive control (MPC) is a sophisticated control that can predict the performance of a process based on the future horizon [271]. The prediction horizon is the extent to which a model can predict the future [272]. The model is used to predict the future based on training data and then take control to deal with predicted future events [273]. ...

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Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey

... In these stigmergic systems the users exploit their digital environment through the use of engineered artefacts that may be annotated with symbolic information representing the human's cognition [7]. Given that the essential capability of any stigmergic system is to transfer the cognitive complexity from the humans to the environment [18], the problem-solving capabilities of the users decisively depend on how the problem is represented in the digital environment. A standard representation of the problem in the environment is realized as a composition of cognitive artefacts linked in a weighted graph. ...

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Swarming Models for Facilitating Collaborative Decisions

... On another note, work on collective cognitive convergence [41] and opinion sharing [19] shows that consensus towards a certain "correct" opinion or cognitive state is always possible yet dependent on noise, variability, and awareness of agents. In [20], the authors show that learning about an exogenous correct state of the world (represented by bits) under confidence was possible but only if the agents were not too confident. ...

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Mixing Dyadic and Deliberative Opinion Dynamics in an Agent-Based Model of Group Decision-Making

... Temporal.-Self-organization is a process that takes place through time, and an adequate formalization of self-organizing systems must support reasoning about the temporal dimension. In many cases, systems need to predict their own behavior in order to adapt appropriately [30,63,97,102,131], but the nonlinear nature of component interactions means that trajectories diverge over time, leading to a prediction horizon [98] beyond which any prediction is essentially random. Estimating this horizon is critical to scoping the predictive activity of a system, and quantifying the uncertainty that is inevitable in a self-organizing system [123]. ...

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Software Engineering for Self-Organizing Systems

... SCAMP exploits a wide range of techniques that the author and previous colleagues 2 developed in stigmergic MASs, in which agents coordinate their activity by making and sensing changes in a shared environment. The environments in these systems included not only spatial lattices [49], where stigmergy is widely used in robotics, but also hierarchical task networks [46] and directed graphs of events [48]. The last of these satisfies our definition for the structural component of a GCM (Sect. ...

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How to turn an MAS into a graphical causal model

... Examples for such scenarios include massive-scale Peer-to-Peer overlay topologies, sensor networks or Big Data scenarios in which graph or network data has to be partitioned across a large number of computing nodes. Recently, such scenarios have been addressed by fully distributed network analysis and data mining techniques, addressing, e.g., cluster detection, graph partitioning or machine learning [10,12,13,15], Contributing to this body of work, in this paper we propose a new fully distributed algorithm for cluster detection in networked systems. It is based on the fact that cluster structures leave their traces in the evolution of self-organized synchronization processes in complex networks. ...

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Decentralized Cluster Detection in Distributed Systems Based on Self-Organized Synchronization

... As noted in the introduction, self-organization is unavoidable in distributed systems, especially open ones, such as networks [15,61,64,123] and water distribution [42], and highly desirable in managing large numbers of robots [53-55, 118, 120] and in agile manufacturing settings [19,94,109,132], where it competes with hierarchical control systems, including holonic schemes [26,133] that we would consider self-adaptive but not selforganizing. In purely informational settings self-organization has been used to coordinate multiple theorem provers [36], to enable documents to organize themselves [104] and find likely users [20,62], and to reassign tasks among agents [31,88]. Mechanisms inspired by wasps and termites have been demonstrated for self-organized construction of physical systems [140]. ...

Reference:

Software Engineering for Self-Organizing Systems