Robotic ubiquitous cognitive ecology for smart homes

Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work

Ab Initio Modeling of Ecosystems with Artificial Life

Artificial Life provides the opportunity to study the emergence and evolution of simple ecosystems in real time. We give an overview of the advantages and limitations of such an approach, as well as its relation to individual-based modeling techniques. The Digital Life system Avida is introduced and prospects for experiments with ab initio evolution (evolution "from scratch"), maintenance, as well as stability of ecosystems are discussed.Comment: 13 pages, 2 figure

Computational evolution of decision-making strategies

Most research on adaptive decision-making takes a strategy-first approach, proposing a method of solving a problem and then examining whether it can be implemented in the brain and in what environments it succeeds. We present a method for studying strategy development based on computational evolution that takes the opposite approach, allowing strategies to develop in response to the decision-making environment via Darwinian evolution. We apply this approach to a dynamic decision-making problem where artificial agents make decisions about the source of incoming information. In doing so, we show that the complexity of the brains and strategies of evolved agents are a function of the environment in which they develop. More difficult environments lead to larger brains and more information use, resulting in strategies resembling a sequential sampling approach. Less difficult environments drive evolution toward smaller brains and less information use, resulting in simpler heuristic-like strategies.Comment: Conference paper, 6 pages / 3 figure

The extended narrotype: adaptation and stasis in spatial evolution.

We present the proposition that features of work spaces, in both learning spaces and offices, might be considered as the memetic or linguistic analogue of extended phenotypes. We demonstrate a synchronicity in theorising about, on the one hand processes of cognition and learning, and on the other about the design of physical space in our two chosen contexts. The actual physical expression lags the theory in both because, we argue, it reflects the narratives of both powerful occupiers of the space and the professional departments responsible for provision of same. The results are compatible with, and an independent argument for, a ‘narrative ecology’ perspective on organisations. Our intention here is the theory however the results have relevance both to accelerating learning and democratizing management. They argue for the spatial dimension to organisational studies as a subset of research and practice in organisational Darwinism

Interpreting Economic Change: Evolution, Structures and Games

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Learning in evolutionary environments

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An Emergent Economics of Ecosystem Management

Economics is an evolving and emerging field of study, so is the management of ecosystems. As such, this paper delineates the co-evolution of economic evaluation that reflects the various recognized ecosystem management approaches of anticipative, adaptive and capacitive ecosystem management. Each management approach is critiqued and from this theoretical analysis an emergent approach for the management of ecosystem is put forward, which accordingly suggests an alternative methodological approach for economic evaluations.Complexity, creativity, economic evaluation, ecosystem management, evolution, open systems, rationality, Resource /Energy Economics and Policy,

Ecologies of Practice in Musical Performance

This article presents an ecological model of musical performance drawn from the field of Gibsonian Ecological Psychology and the techniques of Actor-Network Theory as explicated by Bruno Latour and others. Citing a wide body of empirical research, it is argued that musicians and their musical instruments exist in an ecological relationship at the level of embodied gesture. Furthermore, it is proposed that every act of musicking amounts to a construction of a network of actors that define an “Ecology of Practice,” a thick description more fully encompassing the complexities of musicking than traditional notions of performance practice.Cet article présente un modèle écologique de l’interprétation musicale inspiré du champ de la psychologie écologique gibsonienne et des techniques de la théorie de l’acteur- réseau telle que définie par Bruno Latour et d’autres. Sur la base d’un large corpus de recherche empirique, il avance que les musiciens et leurs instruments existent dans une relation écologique au niveau du geste incarné. En outre, il propose que chaque acte consistant à jouer de la musique corresponde à la construction d’un réseau d’acteurs qui définissent une « écologie de la pratique », description dense qui englobe plus pleinement les complexités du fait de jouer de la musique que les notions de pratiques performancielles