Limiting concept spread in environments with interacting concepts

The propagation of concepts in a population of agents is a form of influence spread, which can be modelled as a cascade from an initial set of individuals. In real-world environments there may be many concepts spreading and interacting. Previous work does not consider utilising concept interactions to limit the spread of a concept. In this paper we present a method for limiting concept spread, in environments where concepts interact and do not block others from spreading. We define a model that allows for the interactions between any number of concepts to be represented and, using this model, develop a solution to the influence limitation problem, which aims to minimise the spread of a target concept through the use of a secondary inhibiting concept. We present a heuristic, called maximum probable gain, and compare its performance to established heuristics for manipulating influence spread in both simulated smallworld networks and real-world networks

Designing the printed book as an interactive environment

Reading a book demands a certain level of interaction from the reader. The cover must be opened and pages turned to navigate the information inside. Conventions have been developed over the life of the book to assist the reader in this navigation and provide orientation. The evolution of electronic reading material has given readers greater opportunities for interacting with their reading material, but many readers still prefer reading from a printed book. This paper investigates how the interactive organizational paradigm of hypertext can be implemented in a printed book to give the reader the opportunity for greater interaction and benefit from some of the advantages that electronic reading environments provide. The investigation in this paper follows an iterative design process in consultation with a panel of four experts. Through four rounds of consultation and refinement two potential solutions were developed for the incorporation of hypertext methods in a printed book

Indirect influence manipulation with partially observable networks

The propagation of concepts through a population of agents can be modelled as a cascade of influence spread from an initial set of individuals. In real-world environments there may be many concepts spreading and interacting, and we may not be able to directly control the target concept we wish to manipulate, requiring indirect manipulation through a secondary controllable concept. Previous work on influence spread typically assumes that we have full knowledge of a network, which may not be the case. In this paper, we investigate indirect influence manipulation when we can only observe a sample of the full network. We propose a heuristic, known as Target Degree, for selecting seed nodes for a secondary controllable concept that uses the limited information available in a partially observable environment to indirectly manipulate the target concept. Target degree is shown to be effective in synthetic small-world networks and in real-world networks when the controllable concept is introduced after the target concept

Manipulating concept spread using concept relationships

The propagation of concepts in a population of agents is a form of influence spread, which can be modelled as a cascade from a set of initially activated individuals. The study of such influence cascades, in particular the identification of influential individuals, has a wide range of applications including epidemic control, viral marketing and the study of social norms. In real-world environments there may be many concepts spreading and interacting. These interactions can affect the spread of a given concept, either boosting it and allowing it to spread further, or inhibiting it and limiting its capability to spread. Previous work does not consider how the interactions between concepts affect concept spread. Taking concept interactions into consideration allows for indirect concept manipulation, meaning that we can affect concepts we are not able to directly control. In this paper, we consider the problem of indirect concept manipulation, and propose heuristics for indirectly boosting or inhibiting concept spread in environments where concepts interact. We define a framework that allows for the interactions between any number of concepts to be represented, and present a heuristic that aims to identify important influence paths for a given target concept in order to manipulate its spread. We compare the performance of this heuristic, called maximum probable gain, against established heuristics for manipulating influence spread

Pragmatism and the pragmatic turn in cognitive science

This chapter examines the pragmatist approach to cognition and experience and provides some of the conceptual background to the “pragmatic turn” currently underway in cognitive science. Classical pragmatists wrote extensively on cognition from a naturalistic perspective, and many of their views are compatible with contemporary pragmatist approaches such as enactivist, extended, and embodied-Bayesian approaches to cognition. Three principles of a pragmatic approach to cognition frame the discussion: First, thinking is structured by the interaction of an organism with its environment. Second, cognition develops via exploratory inference, which remains a core cognitive ability throughout the life cycle. Finally, inquiry/problem solving begins with genuinely irritating doubts that arise in a situation and is carried out by exploratory inference

Authoring a Web‐enhanced interface for a new language‐learning environment

This paper presents conceptual considerations underpinning a design process set up to develop an applicable and usable interface as well as defining parameters for a new and versatile Computer Assisted Language Learning (CALL) environment. Based on a multidisciplinary expertise combining Human Computer Interaction (HCI), Web‐based Java programming, CALL authoring and language teaching expertise, it strives to generate new CALL‐enhanced curriculum developments in language learning. The originality of the approach rests on its design rationale established on the strength of previously identified student requirements and authoring needs identifying inherent design weaknesses and interactive limitations of existing hypermedia CALL applications (Hémard, 1998). At the student level, the emphasis is placed on three important design decisions related to the design of the interface, student interaction and usability. Thus, particular attention is given to design considerations focusing on the need to (a) develop a readily recognizable, professionally robust and intuitive interface, (b) provide a student‐controlled navigational space based on a mixed learning environment approach, and (c) promote a flexible, network‐based, access mode reconciling classroom with open access exploitations. At the author level, design considerations are essentially orientated towards adaptability and flexibility with the integration of authoring facilities, requiring no specific authoring skills, to cater for and support the need for a flexible approach adaptable to specific language‐learning environments. This paper elaborates on these conceptual considerations within the design process with particular emphasis on the adopted principled methodology and resulting design decisions and solutions

Modeling, Simulation and Emulation of Intelligent Domotic Environments

Intelligent Domotic Environments are a promising approach, based on semantic models and commercially off-the-shelf domotic technologies, to realize new intelligent buildings, but such complexity requires innovative design methodologies and tools for ensuring correctness. Suitable simulation and emulation approaches and tools must be adopted to allow designers to experiment with their ideas and to incrementally verify designed policies in a scenario where the environment is partly emulated and partly composed of real devices. This paper describes a framework, which exploits UML2.0 state diagrams for automatic generation of device simulators from ontology-based descriptions of domotic environments. The DogSim simulator may simulate a complete building automation system in software, or may be integrated in the Dog Gateway, allowing partial simulation of virtual devices alongside with real devices. Experiments on a real home show that the approach is feasible and can easily address both simulation and emulation requirement

Challenges in Complex Systems Science

FuturICT foundations are social science, complex systems science, and ICT. The main concerns and challenges in the science of complex systems in the context of FuturICT are laid out in this paper with special emphasis on the Complex Systems route to Social Sciences. This include complex systems having: many heterogeneous interacting parts; multiple scales; complicated transition laws; unexpected or unpredicted emergence; sensitive dependence on initial conditions; path-dependent dynamics; networked hierarchical connectivities; interaction of autonomous agents; self-organisation; non-equilibrium dynamics; combinatorial explosion; adaptivity to changing environments; co-evolving subsystems; ill-defined boundaries; and multilevel dynamics. In this context, science is seen as the process of abstracting the dynamics of systems from data. This presents many challenges including: data gathering by large-scale experiment, participatory sensing and social computation, managing huge distributed dynamic and heterogeneous databases; moving from data to dynamical models, going beyond correlations to cause-effect relationships, understanding the relationship between simple and comprehensive models with appropriate choices of variables, ensemble modeling and data assimilation, modeling systems of systems of systems with many levels between micro and macro; and formulating new approaches to prediction, forecasting, and risk, especially in systems that can reflect on and change their behaviour in response to predictions, and systems whose apparently predictable behaviour is disrupted by apparently unpredictable rare or extreme events. These challenges are part of the FuturICT agenda