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

The Cognitive Ecology of the Internet

In this chapter, we analyze the relationships between the Internet and its users in terms of situated cognition theory. We first argue that the Internet is a new kind of cognitive ecology, providing almost constant access to a vast amount of digital information that is increasingly more integrated into our cognitive routines. We then briefly introduce situated cognition theory and its species of embedded, embodied, extended, distributed and collective cognition. Having thus set the stage, we begin by taking an embedded cognition view and analyze how the Internet aids certain cognitive tasks. After that, we conceptualize how the Internet enables new kinds of embodied interaction, extends certain aspects of our embodiment, and examine how wearable technologies that monitor physiological, behavioral and contextual states transform the embodied self. On the basis of the degree of cognitive integration between a user and Internet resource, we then look at how and when the Internet extends our cognitive processes. We end this chapter with a discussion of distributed and collective cognition as facilitated by the Internet

Cognitive ecology in the information society

Além da dimensão econômica e suas implicações, a Sociedade da Informação traz mudanças na forma em que interpretamos o mundo, impacta nosso ambiente interior e põe novos desafios a nossas relações sociais. O surgimento de novos modos de cognição, a busca de novos modos de vida – vida interior –, e um foco humanista na interação entre a tecnologia e as necessidades sociais são algumas destas dimensões pouco exploradas.Beyond the economical dimension and its consequences, Information Society brings about changes to the way we interpret the world, it impacts our inner environment and poses new challenges to our social relations. The emergence of alternative cognitive paths, the search for new ways of life – inner life –, and a human focus on the interaction of technologies and social needs, are some of those forgotten dimensions

The Cognitive Ecology of Problem Solving

This chapter examines the first goal: understanding real-world problem solving. It is particularly concerned with issues of representativeness and what has been called ecological validity. In addition, because there is considerable evidence that there are differences across the adult life span in solving problems, as reviewed by Botwinick (1978), Giambra and Arenberg (1980), and Rabbitt (1977), it will be important to ask whether or not age is an important qualifier to the conclusions that are reached. The first section discusses the problems people actually face and reviews the paradigms used in scientific investigations to represent problems, including studies of age differences and changes in problem solving. The second section explores the extent to which the lay and scientific domains overlap and finds that there is little overlap. The final section describes an explanatory study of problems representative of those people report facing in everyday life

It began in ponds and rivers : charting the beginnings of the ecology of fish cognition

But fish cognitive ecology did not begin in rivers and streams. Rather, one of the starting points for work on fish cognitive ecology was work done on the use of visual cues by homing pigeons. Prior to working with fish, Victoria Braithwaite helped to establish that homing pigeons rely not just on magnetic and olfactory cues but also on visual cues for successful return to their home loft. Simple, elegant experiments on homing established Victoria's ability to develop experimental manipulations to examine the role of visual cues in navigation by fish in familiar areas. This work formed the basis of a rich seam of work whereby a fish's ecology was used to propose hypotheses and predictions as to preferred cue use, and then cognitive abilities in a variety of fish species, from model systems (Atlantic salmon and sticklebacks) to the Panamanian Brachyraphis episcopi. Cognitive ecology in fish led to substantial work on fish pain and welfare, but was never left behind, with some of Victoria's last work addressed to determining the neural instantiation of cognitive variation.Publisher PDFPeer reviewe

Cognitive Ecology of Color Vision in Orchid Bees

Animals interact with their environment and acquire information from it. Information can be processed by their sensory systems and influence behavior, often mediated through mechanisms of decision-making and learning. Animal pollinators acquire information from flowers and use this information to make decisions about the flowers they visit. My research aimed to understand the role of color vision in a tropical pollinator, the orchid bee Euglossa dilemma. Chapter 1 is a review exploring pollination through the lens of prepared learning. Prepared learning proposes that animals learn some associations better than others due to an evolved match with the environment. I offer a brief history of the concept, build a conceptual framework, explore examples of prepared learning in pollination, and suggest future directions for the field. Chapter 2 characterizes color vision in the orchid bee Euglossa dilemma. I compare E. dilemma\u27s color vision to other related bees by comparing their spectral sensitivity curves and opsin protein amino acid sequences. My results show that E. dilemma is a trichromat, with peaks of Green, Blue, and Ultraviolet in similar regions to other bees. Ultraviolet photoreceptors are the most conserved among the compared bees, while blue photoreceptors and opsin proteins are the least conserved. Chapters 3 explores orchid bee color vision use, focusing on color choice and preference. Color choice was affected by time of day and humidity, and individual orchid bees show variability in their color preferences. Color preference was not affected by the abiotic or biotic factors measured nor predicted by a bee\u27s first choice. Chapter 4 tests whether the presence of scent affects the bees’ choices in color preference trials. Scent affected motivation to engage, but not participation or color preference. I also tested for the ability to condition a sugar reward to a scent cue but did not detect scent learning. My results show that male orchid bees attend to scent cues, delaying their choices about color cues when scent is present. The results from this dissertation add to our knowledge of bee decision-making, and the methodologies developed and implemented here can be used in other populations of wild bees

Cognitive ecology – ecological factors, life-styles and cognition

Cognitive ecology integrates cognition, ecology and neurobiology in one topic and has recently broadened into an exciting diversity of themes covering the entire range of cognition and ecological conditions. The review identifies three major environmental factors interacting with cognition: environmental variation (predictable and unpredictable), environmental complexity and predation. Generally, variable environments favour cognitive abilities such as exploration, learning, innovation, memory and also result in larger brains as compared to stable environments. Likewise, cognition is enhanced in complex versus simple environments, whereas the relationship between predation and cognitive abilities can be positive or negative. However, organisms have often evolved entire life-styles (e.g. residency vs migration, food-caching vs non-caching, generalism vs specialism) to deal with these environmental factors. Considering cognition within this framework provides a much more diverse picture of how cognitive abilities evolved in conjunction with other adaptations to environmental challenges. This integrated approach identifies gaps of knowledge and allows the formulation of hypotheses for future testing. Several recently emerged approaches study cognitive abilities at a new and in part highly integrated level. For example, the effect that environment has on the development of cognitive abilities during ontogeny will improve our understanding about cause and effect and gene x environment interactions. Together with two recently emerged highly integrative approaches that link personality and pace-of-life syndromes with cognitive ecology these new directions will improve insight how cognition is interlinked with other major organisational processes

Bee positive: the importance of electroreception in pollinator cognitive ecology

International audienceThe global atmospheric circuit generates a permanent electric field between the Earth surface and outer atmosphere (Rycroft et al., 2000). The ground and plants conductively linked to it are negatively charged (Bowker and Crenshaw, 2007), whereas animals build up positive charge as they move in contact with air molecules (Jackson and McGonigle, 2005). Electric fields emanating from plants and pollinators, such as bees, are believed to promote pollination by enabling pollen grains to " jump " from flowers to pol-linators and vice versa (Corbet et al., 1982). Two recent studies reveal that bees not only detect these electric fields but also learn to discriminate them, indicating that electroreception should be seriously considered alongside vision and olfaction when studying bee behavior and ecology. Writing in Science, Clarke et al. (2013) demonstrated that bumblebees (Bombus terrestris) detect electric fields around plants and learn to use them to decide whether or not to visit flowers. Using a Faraday pail to measure electric fields generated by bees and plants, the team described how a bee visit temporarily modifies the electric charge of (Petunia) flowers, suggesting that floral electric properties could be used by future visitors to assess the reward value without necessarily needing to probe the flower. To explore this possibility, the authors used differential conditioning in which bees were trained to associate an electrically charged feeder (30 V) with a sucrose reward (CS+) and an uncharged feeder with an aversive quinine solution (CS−). After extensive training (50 trials), bees chose the rewarding feeder in around 80% of trials. Similar levels of performance were observed when bees were trained with two feeders carrying the same charge but different electric field patterns (homogeneous vs. bull's eye shape), indicating that these insects can learn both the magnitude and geometry of an electric field. Bees learned to perform even better in discrimination tasks if the two feeders differed both in color (shade of green) and their electric field pattern compared to if they differed only in color. Natural electric fields around flowers may therefore contribute to the multimodal sources of information that bees use to learn and memorize floral rewards, in conjunction with color, pattern, shape, texture

Situating machine intelligence within the cognitive ecology of the Internet

The Internet is an important focus of attention for the philosophy of mind and cognitive science communities. This is partly because the Internet serves as an important part of the material environment in which a broad array of human cognitive and epistemic activities are situated. The Internet can thus be seen as an important part of the 'cognitive ecology' that helps to shape, support and (on occasion) realize aspects of human cognizing. Much of the previous philosophical work in this area has sought to analyze the cognitive significance of the Internet from the perspective of human cognition. There has, as such, been little effort to assess the cognitive significance of the Internet from the perspective of 'machine cognition'. This is unfortunate, because the Internet is likely to exert a significant influence on the shape of machine intelligence. The present paper attempts to evaluate the extent to which the Internet serves as a form of cognitive ecology for synthetic (machine-based) forms of intelligence. In particular, the phenomenon of Internet-situated machine intelligence is analyzed from the perspective of a number of approaches that are typically subsumed under the heading of situated cognition. These include extended, embedded, scaffolded and embodied approaches to cognition. For each of these approaches, the Internet is shown to be of potential relevance to the development and operation of machine-based cognitive capabilities. Such insights help us to appreciate the role of the Internet in advancing the current state-of-the-art in machine intelligence