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This chapter argues that functional properties are not the only properties that can be realized by other properties, and are not a distinct ontological category of properties. The ‘mixed view’ that functional properties have their causal profiles essentially while other properties have their causal profiles contingently has the unacceptable consequence that we can have no good reason for assigning any property to either of these categories. And on the view that all properties have their causal profiles, essentially there is no basis for marking off functional properties as a separate class. The existence of emergent properties is argued to be compatible with physicalism. The chapter ends with a discussion of how genuine properties can be distinguished from arbitrary disjunctions of properties.

A high-level phenomenon is strongly emergent with respect to a low-level domain when the high-level phenomenon arises from the low-level domain, but truths concerning that phenomenon are not deducible even in principle from truths in the low-level domain. Strong emergence is the notion of emergence that is most common in philosophical discussions of emergence, and is the notion invoked by the British emergentists of the 1920s. A high-level phenomenon is weakly emergent with respect to a low-level domain when the high-level phenomenon arises from the low-level domain, but truths concerning that phenomenon are unexpected given the principles governing the low-level domain. Weak emergence is the notion of emergence that is most common in recent scientific discussions of emergence, and is the notion that is typically invoked by proponents of emergence in complex systems theory. In a way, the philosophical morals of strong emergence and weak emergence are diametrically opposed.

Even if powers are not reducible to non-power properties, still a human agent's abilities to act might be reducible to microproperties, which would leave the agent himself devoid of a truly causal role. This worry is addressed by arguing that the human agent's abilities to act are systemic emergent properties, which are not reducible to the possession of microproperties by his parts. It is further shown that Jaegwon Kim's argument about downward causation does not establish that the agent's active powers must be epiphenomal.

This chapter is concerned with the topic of emergent properties of technical artifacts. It suggests that three issues related to the occurrence of emergent features in technical systems are particularly important in engineering practice: emergent causal powers, the tension between emergent features and functional decomposition, and the unexpectedness and/or unpredictability of emergent features. It analyzes the possible effect of weak and strong forms of epistemic emergence for the control paradigm. This chapter argues that it is a mistake to assume that weak epistemic emergence implies unexpectedness and on that ground poses a threat to the control paradigm.

What are neural network models, what kind of cognitive processes can they perform, and what do they teach us about representations and consciousness? First, this chapter explains the functioning of reduced neuron models. We construct neural networks using these building blocks and explore how they accomplish memory, categorization and other tasks. Computational advantages of parallel-distributed networks are considered, and we explore their emergent properties, such as in pattern completion. Artificial neural networks appear instructive for understanding consciousness, as they illustrate how stable representations can be achieved in dynamic systems. More importantly, they show how low-level processes result in high-level phenomena such as memory retrieval. However, an essential remaining problem is that neural networks do not possess a mechanism specifying what kind of information (e.g. sensory modality) they process. Going back to the classic labeled-lines hypothesis, it is argued that this hypothesis does not offer a solution to the question how the brain differentiates the various sensory inputs it receives into distinct modalities. The brain is observed to live in a "Cuneiform room" by which it only receives and emits spike messages: these are the only source materials by which it can construct modally differentiated experiences.

This chapter offers a way of understanding the effects of poetic images (metaphorical or literal). It employs and extends the notion of ‘emergent properties’, as well as relevance theory’s account of how communicative acts can ‘show’ as much as they mean. The images examined are from poems by Mary Oliver (‘Wings’, ‘Wild Geese’, and ‘Mindful’). The chapter suggests that such poetry is particularly in need of a new theoretical approach capable of engaging with its focus on embodied experience and ‘merging’ with nature. It shows how ‘emergent properties’—for example, a complex sense of what continuity with nature might feel like—can result from engaging in a range of imaginary sensorimotor experiences. The final section of the chapter turns to an abstract painting by Natalia Wróbel which dialogues with Oliver’s poetry, and fleshes out the relevance theory account of communicative showing to articulate differences between artistic genres and media.

This chapter explores the development of physiology and the reductionist aspirations of nineteenth-century physiology. It is shown that the scientific standing of physiology is not dependent on the extent to which it can be reduced to the physical and material sciences, and that the distinctiveness of the life sciences, what marks them out as autonomous with respect to the physical and material sciences, does not depend on their ability to secure the existence of some non-physical force which distinctively shapes and guides biological processes. A central argument is that the notion of emergent properties, rather than being an alternative to reductionism, is actually designed to save it, and that, from an explanatory point of view, it is empty. At the same time, the attempt to formulate questions of emergent properties in terms of ontology is a criticized as a way of thinking about scientific explanation.

This chapter explores a number of issues surrounding the term “supervenience” as related to “emergentism,” and discusses topics such as emergent properties, reductionism, why consciousness is an irreducible feature of physical reality, why this irreducibility has no deep consequences, and supervenience. By definition, consciousness is a causally emergent property of systems, just as solidity, liquidity, and transparency are examples of causally emergent system features. The existence of consciousness can be explained by the causal interactions between elements of the brain at the micro level, but it cannot itself be deduced or calculated from the sheer physical structure of the neurons without some additional account of the causal relations between them.

This book introduces a conceptual framework for brain function based on large populations of neurons. It advances the hypothesis that emergent properties are high-level effects that depend on lower-level phenomena in some systematic way, drawing on the idea that brains are computational in nature. Areas and topics related to computational neuroscience covered in this book include computational mechanisms in neurons, analysis of signal processing in neural circuits, representation of sensory information, systems models of sensorimotor integration, and computational approaches to plasticity. The book emphasizes the importance of single neuron models as the foundation into which network models must eventually fit. It also provides a background discussion on neuroscience and the science of computation.

This chapter explains the considerable difficulty we have in making sense of the world and finding our place in it. To undertake that task we need to start with the most basic questions about how we gain knowledge of the world (epistemology), including the limits on our senses and the inevitable ways we form mental images that shape our understandings. It explores longstanding issues of the composition of the world (metaphysics), particularly the challenges of coming to terms with intangibles, along with the limits on human rationality and the inevitable origins of normativity in human sentiment, genetics, and cultural inertia. It takes up the cultural disorientation brought on by the decline of religion and the claims of Darwin, Freud, Einstein and others leading to the pessimism of such works as Krutch, The Modern Temper from the 1920s. It reviews the three basic definitions of truth, considers how the parts of nature form wholes with emergent properties, considers intangibles and continued claims for the objective reality of morals, and challenges the misleading claims about the social construction of nature. All of this supplies a foundation for a critique of prevailing culture and key institutions and calls for cultural reform.

Through introducing the key concepts that are foundational to an understanding of complexity theory and its relevance to criminal justice and social work, Chapter One provides important contextual information for the following chapters in the book. The chapter aims to familiarise readers with the vocabulary of complexity theory as a branch of the study of NDS, including notions of complex deterministic systems, attractors, non-linearity, chaos, self-organisation, emergent properties and adaptation. The chapter will also explore the background to key debates in the study of complexity by considering, for example, the highly contested relevance of mathematically derived notions of chaos to the reality of being human. Different approaches to these areas of study are (broadly) defined by positivism, post-positivism, and constructivism.

This chapter returns to the question of literary ‘images’ in relation to the everyday use of figures, arguing that they are not ‘pictures’, but sensory imaginings, affordances serving cognitive ends. The chapter focuses on small-scale examples (metaphors and other figures) drawn primarily from lyric poetry. It introduces some key arguments and terms from relevance theory: among these, the most salient are the term ‘implicatures’, and especially the phrase ‘array of implicatures’, which relevance theorists use to characterize certain kinds of poetic effect; the notion of ‘ad hoc concept’, which brings out the extent to which metaphor (like catachresis) is a mode of word-formation; and the expression ‘emergent properties’, which describes the way in which meaning emerges in the formation of an ad hoc concept. The chapter proposes a general ‘passing theory’ of figurative language, in which meanings are incrementally updated in a dynamic process of comprehension.

Organisms that developed independent existence had to rely on external sources of energy and, in plants, photosynthesis was probably the end of an evolutionary process that saw cells free living in sunlight. How did this process evolve? The earliest organisms thought to be bacteria are potentially detectable 3.5 billion years ago. Photosynthesis commenced about 3 billion years ago or so with oxygen-producing organisms in abundance 2.7 billion years ago. Fossil stromatolites, 2.2 billion years old, and containing blue-green algae and bacteria are well established, and, astonishingly, are very similar to present-day stromatolites. What provided the impetus for early molecular primordia to eventually generate a living cell? A robust energy supply is undoubtedly essential. Early chemical reactions would have to be coupled directly or indirectly to it. Providing the energy supply is sustained, Prigogine’s dissipative mechanism, seeing order derive increasingly from continued energy flow, is the crucial underpin. The early molecular components would have to be connected to form an integrated, holistic system of low entropy and information flow between them. With increasing experimentation, a stabilizing hierarchical structure would come to dominate, initially, between molecules, then groups of molecules as modules. This early system had to become teleonomic; that is being purposive in maintenance and replication. Negative feedback would have helped stabilize the early structure by keeping the internal environment constant, but may have evolved to counteract destabilizing noise. Each of these criteria is discussed in this chapter to try and provide understanding of this vital event.

Simple or ‘complicated’ systems that display linear, predictable behaviours are contrasted with complex systems characterised by ‘emergent properties’ arising from inter-relationships between parts, feedback loops and sometimes unexpected effects arising from changes in other parts of the system. Particular characteristics of complex social systems and learning from change processes in complex social systems are described. The relevance of systems thinking to epidemiology, public health research and ‘evidence’ is noted including the importance of recognising wider context, the relationship between knowledge and uncertainty and development of new methodologies. It is noted that approaches to public health such as socio-ecological, community development and policy, regulation and ‘whole organisation’ approaches show some features of systemic approaches but that this is not always explicit or consistent. Opportunities and barriers to further development of systemic approaches to public health in the new organisational arrangements for public health in England are highlighted.

The relationships among mind, self, conscious thought, discursive reasoning, and social context became central issues in nineteenth- and twentieth-century psychology, linguistics, sociology, and epistemology, with direct implications for the nature of scientific knowledge. Minds and selves can be conceptualized as expressions of interactions between an individual’s nervous system and their physical and social environment. Is conscious thought, and in particular discursive reasoning, under the control of the individual thinker, or does it reflect societal influences? Nineteenth-century experimental neurophysiology and psychology began to reveal the role that systemic features of the nervous system and the brain play in producing consciousness. Concurrently, sociologists, psychologists, and linguists were proposing roles for the unconscious, language, society, and innate gestalten in shaping and limiting conscious thought. These ideas converged in the theories of individual scientists.

At first blush, computing and biology seem an odd couple, yet they formed a liaison of sorts from the very first years of the electronic digital computer. Following a seminal paper published in 1943 by neurophysiologist Warren McCulloch and mathematical logician Warren Pitts on a mathematical model of neuronal activity, John von Neumann of the Institute of Advanced Study, Princeton, presented at a symposium in 1948 a paper that compared the behaviors of computer circuits and neuronal circuits in the brain. The resulting publication was the fountainhead of what came to be called cellular automata in the 1960s. Von Neumann’s insight was the parallel between the abstraction of biological neurons (nerve cells) as natural binary (on–off) switches and the abstraction of physical computer circuit elements (at the time, relays and vacuum tubes) as artificial binary switches. His ambition was to unify the two and construct a formal universal theory.One remarkable aspect of von Neumann’s program was inspired by the biology: His universal automata must be able to self-reproduce. So his neuron-like automata must be both computational and constructive. In 1955, invited by Yale University to deliver the Silliman Lectures for 1956, von Neumann chose as his topic the relationship between the computer and the brain. He died before being able to deliver the lectures, but the unfinished manuscript was published by Yale University Press under the title The Computer and the Brain (1958). Von Neumann’s definitive writings on self-reproducing cellular automata, edited by his one-time collaborator Arthur Burks of the University of Michigan, was eventually published in 1966 as the book Theory of Self-Reproducing Automata. A possible structure of a von Neumann–style cellular automaton is depicted in Figure 7.1. It comprises a (finite or infinite) configuration of cells in which a cell can be in one of a finite set of states. The state of a cell at any time t is determined by its own state and those of its immediate neighbors in the preceding point of time t – 1, according to a state transition rule.

Holland describes emergence in rule-governed systems as "the recognizable features and patterns" that derive from the operation of systems for which we have "useful descriptions in terms of rules or laws" [8, p. 3-4]. He says that, "Emergent phenomena also occur in domains for which we presently have few accepted rules; ethical systems, the evolution of nations, and the spread of ideas come to mind. Most of the ideas developed here have relevance for such systems, but precise application to such systems will require better conjectures about the laws (if any) that govern their development" [8, p. 3]. Our goal in this chapter is to extend the notions of emergence proposed by Holland to allow for the study of emergent properties in the development of this latter class of systems. In particular, we are interested in the investigation of the laws that underlie the development of cultural systems. One thing that all cultures have in common is that they can change. Murdoch has stated that, "culture changes; and the process of change appears to be an adaptive one, comparable to evolution in the organic realm but of a different order. Cultures tend, through periods of time, to become adjusted to the geographic environment, as the anthro-geographers have shown, although environmental influences are no longer conceived as determinative of cultural development" [11, p. 51]. The question that we are interested in is how is this adaptive task reflected in the knowledge needed within a given culture? The "laws of cultural change" that will be of interest here are those that govern the knowledge used to adapt a culture to changes in its environment. That is, how do environmental dynamics impact the types of knowledge used by problem-solving agents in an environment. Holland has shown that binary schematic knowledge can play an important role in problem solving via the schema theorem. In that theorem he only addressed the utilization of one knowledge type, binary schemata. Here, we allow problem-solving knowledge to be stored explicitly in terms of several different types of schemata, each of which can be viewed as an extension of the binary approach.