The organisation of sociality: a manifesto for a new science of multi-agent systems

In this paper, we pose and motivate a challenge, namely the need for a new science of multi-agent systems. We propose that this new science should be grounded, theoretically on a richer conception of sociality, and methodologically on the extensive use of computational modelling for real-world applications and social simulations. Here, the steps we set forth towards meeting that challenge are mainly theoretical. In this respect, we provide a new model of multi-agent systems that reflects a fully explicated conception of cognition, both at the individual and the collective level. Finally, the mechanisms and principles underpinning the model will be examined with particular emphasis on the contributions provided by contemporary organisation theory

The emergence of information systems: a communication-based theory

An information system is more than just the information technology; it is the system that emerges from the complex interactions and relationships between the information technology and the organization. However, what impact information technology has on an organization and how organizational structures and organizational change influence information technology remains an open question. We propose a theory to explain how communication structures emerge and adapt to environmental changes. We operationalize the interplay of information technology and organization as language communities whose members use and develop domain-specific languages for communication. Our theory is anchored in the philosophy of language. In developing it as an emergent perspective, we argue that information systems are self-organizing and that control of this ability is disseminated throughout the system itself, to the members of the language community. Information technology influences the dynamics of this adaptation process as a fundamental constraint leading to perturbations for the information system. We demonstrate how this view is separated from the entanglement in practice perspective and show that this understanding has far-reaching consequences for developing, managing, and examining information systems

The value of theoretical multiplicity for steering transitions towards sustainability

Transition management, as a theory of directing structural societal changes towards sustainable system innovations, has become a major topic in scientific research over the last years. In this paper we focus on the question how transitions towards sustainability can be steered, governed or managed, in particular by governmental actors. We suggest an approach of theoretical multiplicity, arguing that multiple theories will be needed simultaneously for dealing with the complex societal sustainability issues. Therefore, we address the steering question by theoretically comparing transition management theory to a number of related theories on societal change and intervention, such as multi-actor collaboration, network governance, configuration management, policy agenda setting, and adaptive management. We conclude that these related theories put the managerial assumptions of transition management into perspective, by adding other steering roles and leadership mechanisms to the picture. Finally we argue that new modes of steering inevitable have consequences for the actual governance institutions. New ways of governing change ask for change within governance systems itself and vice versa. Our argument for theoretical multiplicity implicates the development of multiple, potentially conflicting, governance capacitie

How to study the mind: An introduction to embodied cognition

Embodied Cognition (EC) is a comprehensive approach to, and framework for, the study of the mind. EC treats cognition as a coordinated set of tools evolved by organisms for coping with their environments. Each of the key terms in this characterization-tool, evolved, organism, coping, and environment-has a special significance for understanding the mind that is discussed in this article

Psychological principles of successful aging technologies: A mini-review

Based on resource-oriented conceptions of successful life-span development, we propose three principles for evaluating assistive technology: (a) net resource release; (b) person specificity, and (c) proximal versus distal frames of evaluation. We discuss how these general principles can aid the design and evaluation of assistive technology in adulthood and old age, and propose two technological strategies, one targeting sensorimotor and the other cognitive functioning. The sensorimotor strategy aims at releasing cognitive resources such as attention and working memory by reducing the cognitive demands of sensory or sensorimotor aspects of performance. The cognitive strategy attempts to provide adaptive and individualized cuing structures orienting the individual in time and space by providing prompts that connect properties of the environment to the individual's action goals. We argue that intelligent assistive technology continuously adjusts the balance between `environmental support' and `self-initiated processing' in person-specific and aging-sensitive ways, leading to enhanced allocation of cognitive resources. Furthermore, intelligent assistive technology may foster the generation of formerly latent cognitive resources by activating developmental reserves (plasticity). We conclude that `lifespan technology', if co-constructed by behavioral scientists, engineers, and aging individuals, offers great promise for improving both the transition from middle adulthood to old age and the degree of autonomy in old age in present and future generations. Copyright (C) 2008 S. Karger AG, Basel

Social re-orientation and brain development: An expanded and updated view.

Social development has been the focus of a great deal of neuroscience based research over the past decade. In this review, we focus on providing a framework for understanding how changes in facets of social development may correspond with changes in brain function. We argue that (1) distinct phases of social behavior emerge based on whether the organizing social force is the mother, peer play, peer integration, or romantic intimacy; (2) each phase is marked by a high degree of affect-driven motivation that elicits a distinct response in subcortical structures; (3) activity generated by these structures interacts with circuits in prefrontal cortex that guide executive functions, and occipital and temporal lobe circuits, which generate specific sensory and perceptual social representations. We propose that the direction, magnitude and duration of interaction among these affective, executive, and perceptual systems may relate to distinct sensitive periods across development that contribute to establishing long-term patterns of brain function and behavior

Session 5: Development, Neuroscience and Evolutionary Psychology

Proceedings of the Pittsburgh Workshop in History and Philosophy of Biology, Center for Philosophy of Science, University of Pittsburgh, March 23-24 2001 Session 5: Development, Neuroscience and Evolutionary Psycholog

Memory and information processing in neuromorphic systems

A striking difference between brain-inspired neuromorphic processors and current von Neumann processors architectures is the way in which memory and processing is organized. As Information and Communication Technologies continue to address the need for increased computational power through the increase of cores within a digital processor, neuromorphic engineers and scientists can complement this need by building processor architectures where memory is distributed with the processing. In this paper we present a survey of brain-inspired processor architectures that support models of cortical networks and deep neural networks. These architectures range from serial clocked implementations of multi-neuron systems to massively parallel asynchronous ones and from purely digital systems to mixed analog/digital systems which implement more biological-like models of neurons and synapses together with a suite of adaptation and learning mechanisms analogous to the ones found in biological nervous systems. We describe the advantages of the different approaches being pursued and present the challenges that need to be addressed for building artificial neural processing systems that can display the richness of behaviors seen in biological systems.Comment: Submitted to Proceedings of IEEE, review of recently proposed neuromorphic computing platforms and system