Born to learn: The inspiration, progress, and future of evolved plastic artificial neural networks

Biological plastic neural networks are systems of extraordinary computational capabilities shaped by evolution, development, and lifetime learning. The interplay of these elements leads to the emergence of adaptive behavior and intelligence. Inspired by such intricate natural phenomena, Evolved Plastic Artificial Neural Networks (EPANNs) use simulated evolution in-silico to breed plastic neural networks with a large variety of dynamics, architectures, and plasticity rules: these artificial systems are composed of inputs, outputs, and plastic components that change in response to experiences in an environment. These systems may autonomously discover novel adaptive algorithms, and lead to hypotheses on the emergence of biological adaptation. EPANNs have seen considerable progress over the last two decades. Current scientific and technological advances in artificial neural networks are now setting the conditions for radically new approaches and results. In particular, the limitations of hand-designed networks could be overcome by more flexible and innovative solutions. This paper brings together a variety of inspiring ideas that define the field of EPANNs. The main methods and results are reviewed. Finally, new opportunities and developments are presented

Coordination Under Uncertain Conditions: An Analysis of the Fukushima Catastrophe

This paper analyzes the impacts of the 11 March 2011 earthquake and tsunami at the Fukushima nuclear power plant in Japan, which were amplified by a failure of coordination across the plant, corporate, industrial, and regulatory levels, resulting in a nuclear catastrophe, comparable in cost to Chernobyl. It derives generic lessons for industrial structure and regulatory frame of the electric power industry by identifying the two shortcomings of a horizontal coordination mechanism: instability under large shock and the lack of “defense in depth.”fukushima catastrophe; nuclear power; earthquake and tsunami

Organizations under Large Uncertainty: An Analysis of the Fukushima Catastrophe

This paper analyzes the impacts of the March 11, 2011, earthquake and tsunami at the Fukushima nuclear power plant in Japan, which were amplified by a failure of coordination across the plant, corporate, industrial, and regulatory levels, resulting in a nuclear catastrophe comparable in cost to Chernobyl. It derives generic lessons for industrial structure and regulatory frame for the electric power industry by identifying the two shortcomings of a horizontal coordination mechanism: instability under large shocks and the lack of defense in depth.The suggested policy response is to harness the power of Òopen-interface-rule-based modularity by creating an independent nuclear safety commission and an independent system operator owning the transmission grid module in Japan. We propose a transitory price mechanism that can restrain price volatility while providing investment incentives.horizontal coordination, modularity, nuclear power, regional monopoly, electricity regulation, safety regulation, public ownership, independent system operator

Rational's experience using Ada for very large systems

The experience using the Rational Environment has confirmed the advantages forseen when the project was started. Interactive syntatic and semantic information makes a tremendous difference in the ease of constructing programs and making changes to them. The ability to follow semantic references makes it easier to understand exisiting programs and the impact of changes. The integrated debugger makes it much easier to find bugs and test fixes quickly. Taken together, these facilites have helped greatly in reducing the impact of ongoing maintenance of the ability to produce a new code. Similar improvements are anticipated as the same level of integration and interactivity are achieved for configuration management and version control. The environment has also proven useful in introducing personnel to the project and existing personnel to new parts of the system. Personnel benefit from the assistance with syntax and semantics; everyone benefits from the ability to traverse and understand the structure of unfamiliar software. It is often possible for someone completely unfamiliar with a body of code to use these facilities, to understand it well enough to successfully with a body of code to use these facilities to understand it well enough to successfully diagnose and fix bugs in a matter of minutes

Software development environments: Present and future, appendix D

Computerized environments which facilitate the development of appropriately functioning software systems are discussed. Their current status is reviewed and several trends exhibited by their history are identified. A number of principles, some at (slight) variance with the historical trends, are suggested and it is argued that observance of these principles is critical to achieving truly effective and efficient software development support environments

Global adaptation in networks of selfish components: emergent associative memory at the system scale

In some circumstances complex adaptive systems composed of numerous self-interested agents can self-organise into structures that enhance global adaptation, efficiency or function. However, the general conditions for such an outcome are poorly understood and present a fundamental open question for domains as varied as ecology, sociology, economics, organismic biology and technological infrastructure design. In contrast, sufficient conditions for artificial neural networks to form structures that perform collective computational processes such as associative memory/recall, classification, generalisation and optimisation, are well-understood. Such global functions within a single agent or organism are not wholly surprising since the mechanisms (e.g. Hebbian learning) that create these neural organisations may be selected for this purpose, but agents in a multi-agent system have no obvious reason to adhere to such a structuring protocol or produce such global behaviours when acting from individual self-interest. However, Hebbian learning is actually a very simple and fully-distributed habituation or positive feedback principle. Here we show that when self-interested agents can modify how they are affected by other agents (e.g. when they can influence which other agents they interact with) then, in adapting these inter-agent relationships to maximise their own utility, they will necessarily alter them in a manner homologous with Hebbian learning. Multi-agent systems with adaptable relationships will thereby exhibit the same system-level behaviours as neural networks under Hebbian learning. For example, improved global efficiency in multi-agent systems can be explained by the inherent ability of associative memory to generalise by idealising stored patterns and/or creating new combinations of sub-patterns. Thus distributed multi-agent systems can spontaneously exhibit adaptive global behaviours in the same sense, and by the same mechanism, as the organisational principles familiar in connectionist models of organismic learning

Non rivalry and complementarity in computer software

In this paper we contend that – contrary to what argued by a vast part of the literature – computer software and, more in general, digital goods (i.e. symbolic strings on an electronic medium with some eco- nomic value) do not present the characteristics of a public good as they do not suffer from lack of rivarly and excludability any more than other durable goods which are regularly allocated on competitive markets. We argue instead that the “market allocation problem” – if any – with digital goods does not arise from their public nature but from some pe- culiar characteristics of the production technology. The latter presents the nature of a typical problem solving activity as far as the produc- tion of the first unit is concerned, this means that innovative activities in computer software are characterized by high degrees of interdepen- dencies, cumulativeness, sequentiality, path dependence and, more in general, sub-optimality arising from imperfect problem decompositions. As far as the production of further units is concerned, we observe in- stead high (but not infinite) expansibility and perfect codification (lack of any tacit dimension) which make diffusion costs rapidly fall. Given such claims, we argue that a standard “Coasian” approach to property rights, designed to cope with the externalities of semi-public goods may not be appropriate for computer software, as it may decrease both ex-ante incentives to innovation and ex-post efficiency of diffusion. On the other hand the institutional definition of property rights may strongly influence the patterns of technological evolution and division of labor in directions which are not necessarily optimal.Intellectual property; hierarchies; innovation; software; digital goods

Why study movement variability in autism?

Autism has been defined as a disorder of social cognition, interaction and communication where ritualistic, repetitive behaviors are commonly observed. But how should we understand the behavioral and cognitive differences that have been the main focus of so much autism research? Can high-level cognitive processes and behaviors be identified as the core issues people with autism face, or do these characteristics perhaps often rather reflect individual attempts to cope with underlying physiological issues? Much research presented in this volume will point to the latter possibility, i.e. that people on the autism spectrum cope with issues at much lower physiological levels pertaining not only to Central Nervous Systems (CNS) function, but also to peripheral and autonomic systems (PNS, ANS) (Torres, Brincker, et al. 2013). The question that we pursue in this chapter is what might be fruitful ways of gaining objective measures of the large-scale systemic and heterogeneous effects of early atypical neurodevelopment; how to track their evolution over time and how to identify critical changes along the continuum of human development and aging. We suggest that the study of movement variability—very broadly conceived as including all minute fluctuations in bodily rhythms and their rates of change over time (coined micro-movements (Figure 1A-B) (Torres, Brincker, et al. 2013))—offers a uniquely valuable and entirely objectively quantifiable lens to better assess, understand and track not only autism but cognitive development and degeneration in general. This chapter presents the rationale firstly behind this focus on micro-movements and secondly behind the choice of specific kinds of data collection and statistical metrics as tools of analysis (Figure 1C). In brief the proposal is that the micro-movements (defined in Part I – Chapter 1), obtained using various time scales applied to different physiological data-types (Figure 1), contain information about layered influences and temporal adaptations, transformations and integrations across anatomically semi-independent subsystems that crosstalk and interact. Further, the notion of sensorimotor re-afference is used to highlight the fact that these layered micro-motions are sensed and that this sensory feedback plays a crucial role in the generation and control of movements in the first place. In other words, the measurements of various motoric and rhythmic variations provide an access point not only to the “motor systems”, but also access to much broader central and peripheral sensorimotor and regulatory systems. Lastly, we posit that this new lens can also be used to capture influences from systems of multiple entry points or collaborative control and regulation, such as those that emerge during dyadic social interactions

The link between the diversity of productive models and the variety of capitalisms

Prepared within the framework of the ESEMK project supported by the EU (FP6, Priority 7, CIT-CT-2004-506077 The European Socio-Economic Models of a Knowledge-based society), this paper discusses the linking between the variety of capitalism and the diversity of organisational forms for firms. This linking is illustrated through the case of the car industry. First part presents the works based on the hypothesis of an institutional isomorphism between the macro-level and the organisation. Second part tries to link analytical grids which integrate the diversity of institutional forms at the macro, meso and micro-levels.car industry, institution, institutional isomorphism, organisation of the firm, productive models, sector, variety of capitalism