Dynamic Influence Networks for Rule-based Models

We introduce the Dynamic Influence Network (DIN), a novel visual analytics technique for representing and analyzing rule-based models of protein-protein interaction networks. Rule-based modeling has proved instrumental in developing biological models that are concise, comprehensible, easily extensible, and that mitigate the combinatorial complexity of multi-state and multi-component biological molecules. Our technique visualizes the dynamics of these rules as they evolve over time. Using the data produced by KaSim, an open source stochastic simulator of rule-based models written in the Kappa language, DINs provide a node-link diagram that represents the influence that each rule has on the other rules. That is, rather than representing individual biological components or types, we instead represent the rules about them (as nodes) and the current influence of these rules (as links). Using our interactive DIN-Viz software tool, researchers are able to query this dynamic network to find meaningful patterns about biological processes, and to identify salient aspects of complex rule-based models. To evaluate the effectiveness of our approach, we investigate a simulation of a circadian clock model that illustrates the oscillatory behavior of the KaiC protein phosphorylation cycle.Comment: Accepted to TVCG, in pres

Life is an Adventure! An agent-based reconciliation of narrative and scientific worldviews\ud

The scientific worldview is based on laws, which are supposed to be certain, objective, and independent of time and context. The narrative worldview found in literature, myth and religion, is based on stories, which relate the events experienced by a subject in a particular context with an uncertain outcome. This paper argues that the concept of “agent”, supported by the theories of evolution, cybernetics and complex adaptive systems, allows us to reconcile scientific and narrative perspectives. An agent follows a course of action through its environment with the aim of maximizing its fitness. Navigation along that course combines the strategies of regulation, exploitation and exploration, but needs to cope with often-unforeseen diversions. These can be positive (affordances, opportunities), negative (disturbances, dangers) or neutral (surprises). The resulting sequence of encounters and actions can be conceptualized as an adventure. Thus, the agent appears to play the role of the hero in a tale of challenge and mystery that is very similar to the "monomyth", the basic storyline that underlies all myths and fairy tales according to Campbell [1949]. This narrative dynamics is driven forward in particular by the alternation between prospect (the ability to foresee diversions) and mystery (the possibility of achieving an as yet absent prospect), two aspects of the environment that are particularly attractive to agents. This dynamics generalizes the scientific notion of a deterministic trajectory by introducing a variable “horizon of knowability”: the agent is never fully certain of its further course, but can anticipate depending on its degree of prospect

Simulation Game Concept For AI-Enhanced Teaching Of Advanced Value Stream Analysis and Design

Value stream analysis and design is employed globally by improvement teams within industrial settings to maximize value creation and eliminate waste. For ending methodical time-centricity, research expanded the methodology to incorporate diverse facets like material flow cost accounting, information logistics, and external influence factors. These enhancements, along with increasing data volumes, are prompting a re-evaluation of how professional improvement teams should think and operate. Consequently, a transformation of the pedagogical approach used for educating students and professionals necessitates novel solutions. Conventional teaching methods such as expository lectures are widely considered inadequate in promoting knowledge retention and engagement. So far, existing research has not yet resulted in a solution that can effectively impart the methodological complexity of advanced value stream analysis and design in a motivating and vivid fashion. To address this gap, this paper applies a tailored CRISP gamification framework to develop a simulation game concept. These concept enables AI-enhanced teaching of advanced value stream analysis and design focusing on identification of multi-stage resource-efficient optimization strategies. Through integration of game-based learning with AI a trained reinforcement learning agent can act either competitively or cooperatively, creating a unique form of teaching accounting the aspects personalization, adaptive feedback, content creation, and analysis and assessment

Towards a Complex Adaptive Systems Roadmap for Information Systems Research

Complex adaptive systems (CAS) theory conceptualises a system composed of heterogeneous agents, which interact with each other to adapt to the environment. CAS concepts have been applied in several Information Systems (IS) referent disciplines over the last decade to study complex phenomena in strategic management, social science and organisational research. The application of CAS theory in IS is more recent, wherein researchers have studied complex phenomena including agile processes, systems dynamics and IS alignment. Though CAS has gained some traction with IS researchers, general understanding of the potential of CAS, and its methodological and theoretical applications in IS research, is yet partial and fragmented. The aim of this study is to develop a roadmap for applying CAS in IS research, to analyse the key research objectives with CAS in extant IS research, and to identify methodological and theoretical approaches that researchers follow in conducting CAS-based IS research. To achieve this, we review IS papers published 2002-2014 inclusive in top IS outlets. We analyse the papers based on a supportive theoretical framework and identify eight main objectives of applying CAS, three methodological approaches, and two theoretical approaches related to CAS-based research in the IS discipline. The study reports several valuable observations, including the relative versatility of computational studies over other studies, the minimal use of CAS in design research, methodological triangulation, and theoretical triangulation in IS research. We propose several guidelines for future researchers