EPISTEMIC STIGMERGY: NATURAL VS. ARTIFICIAL INTELLIGENCE

Social Insects : Ecology and Behavioural Biology

1 online resource; Here is a guide to the ecology of social insects. It is intended for general ecologists and entomologists as well as for undergraduates and those about to start research on social insects; even the experienced investigator may find the comparison between different groups of social insects illuminating. Most technical terms are translated into common language as far as can be done without loss of accuracy but scientific names are unavoidable. Readers will become familiar with the name even though they cannot visualize the animal and could reflect that only a very few of the total species have been studied so far! References too are essential and with these it should be possible to travel more deeply into the vast research literature, still increasing monthly. When I have cited an author in another author's paper, this implies that I have not read the original and the second author must take responsi bility for accuracy! Many hands and heads have helped to make this book. I thank all my colleagues past and present for their enduring though critical support, and I thank with special pleasure: E.]. M. Evesham who fashioned the diagrams;]. Free, D.J. Stradling and]. P.E.C. Darlington who supplied photographs; D.Y. Brian and R.A. Weller who were meticulous on the linguistic side; and G. Frith and R.M. Jones who collated the references. List of plates 1. Fungus combs of Acromyrmex octospinosus and Macrotermes michaelseni. 13 2. Mouthparts of larval Myrmica; 1 Introduction -- 2 Food -- 2.1 Termites as decomposers -- 2.2 Wasps and ants as predators -- 2.3 Sugars as fuel save prey -- 2.4 Seed eaters -- 2.5 Leaf eaters -- 2.6 Pollen eaters -- 3 Foraging by individuals -- 3.1 Foraging strategy -- 3.2 Worker variability -- 4 Foraging in groups -- 4.1 Communication about food -- 4.2 Group slave-raiding -- 4.3 Tunnels and tracks -- 4.4 Nomadic foraging -- 5 Cavity nests and soil mounds -- 5.1 Cavities and burrows -- 5.2 Soil mounds -- 6 Nests of fibre, silk and wax -- 6.1 Mounds of vegetation and tree nests -- 6.2 Combs of cells -- 7 Microclimate -- 7.1 Environmental regulation -- 7.2 Metabolic regulation -- 8 Defence -- 8.1 Painful and paralysing injections -- 8.2 Toxic smears and repellants -- 9 Food processing -- 9.1 Mastication, extraction and regurgitation -- 9.2 Yolk food supplements -- 9.3 Head food glands -- 10 Early population growth -- 10.1 Food distribution -- 10.2 Colony foundation -- 10.3 The growth spurt -- 11 Maturation -- 11.1 Simple models of reproduction -- 11.2 Social control over caste -- 11.3 Males in social Hymenoptera -- 11.4 Maturation in general -- 12 Reproduction -- 12.1 Caste morphogenesis -- 12.2 Copulation and dispersal -- 12.3 Production -- 12.4 Summary -- 13 Evolution of insect societies -- 13.1 Theories of individual selection -- 13.2 Models of these theories -- 13.3 Group selection -- 13.4 Conclusions -- 14 Colonies -- 14.1 The colony barrier -- 14.2 Queen number and species ecology -- 14.3 Queen interaction and queen relatedness -- 15 Comparative ecology of congeneric species -- 15.1 Ant and termite races -- 15.2 Desert ants and termites -- 15.3 Ants and termites in grassland -- 15.4 Forest ants and termites -- 15.5 Wasps and bumblebees -- 15.6 Advanced bees -- 16 Communities -- 16.1 Temperate zone communities in grass and woodland -- 16.2 Desert communities -- 16.3 Tropical rain forest -- 16.4 Conclusions -- 17 Two themes -- 17.1 Plant mutualism -- 17.2 Social organization -- References -- Author index

Self-Organization in Biological Systems

The synchronized flashing of fireflies at night. The spiraling patterns of an aggregating slime mold. The anastomosing network of army-ant trails. The coordinated movements of a school of fish. Researchers are finding in such patterns—phenomena that have fascinated naturalists for centuries—a fertile new approach to understanding biological systems: the study of self-organization. This book, a primer on self-organization in biological systems for students and other enthusiasts, introduces readers to the basic concepts and tools for studying self-organization and then examines numerous examples of self-organization in the natural world. Self-organization refers to diverse pattern formation processes in the physical and biological world, from sand grains assembling into rippled dunes to cells combining to create highly structured tissues to individual insects working to create sophisticated societies. What these diverse systems hold in common is the proximate means by which they acquire order and structure. In self-organizing systems, pattern at the global level emerges solely from interactions among lower-level components. Remarkably, even very complex structures result from the iteration of surprisingly simple behaviors performed by individuals relying on only local information. This striking conclusion suggests important lines of inquiry: To what degree is environmental rather than individual complexity responsible for group complexity? To what extent have widely differing organisms adopted similar, convergent strategies of pattern formation? How, specifically, has natural selection determined the rules governing interactions within biological systems? Broad in scope, thorough yet accessible, this book is a self-contained introduction to self-organization and complexity in biology—a field of study at the forefront of life sciences research.

Swarm Intelligence: From Natural to Artificial Systems

Abstract. Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving systems with sophisticated collective intelligence. Co

Functional Information: Towards Synthesis of Biosemiotics and Cybernetics

Biosemiotics and cybernetics are closely related, yet they are separated by the boundary between life and non-life: biosemiotics is focused on living organisms, whereas cybernetics is applied mostly to non-living artificial devices. However, both classes of systems are agents that perform functions necessary for reaching their goals. I propose to shift the focus of biosemiotics from living organisms to agents in general, which all belong to a pragmasphere or functional universe. Agents should be considered in the context of their hierarchy and origin because their semiosis can be inherited or induced by higher-level agents. To preserve and disseminate their functions, agents use functional information - a set of signs that encode and control their functions. It includes stable memory signs, transient messengers, and natural signs. The origin and evolution of functional information is discussed in terms of transitions between vegetative, animal, and social levels of semiosis, defined by Kull. Vegetative semiosis differs substantially from higher levels of semiosis, because signs are recognized and interpreted via direct code-based matching and are not associated with ideal representations of objects. Thus, I consider a separate classification of signs at the vegetative level that includes proto-icons, proto-indexes, and proto-symbols. Animal and social semiosis are based on classification, and modeling of objects, which represent the knowledge of agents about their body (Innenwelt) and environment (Umwelt).

Learning Outside the Brain: Integrating Cognitive Science and Systems Biology

Learning is commonplace in organisms such as ourselves and even in organisms as far distant as the bee and the octopus. Such learning is implemented by brains, or neuronal networks, and has been extensively studied within ethology, psychology, cognitive science, and neuroscience. Whether learning also takes place in nonneuronal settings has remained a matter of sustained controversy, too often dominated by ideological views. In this survey, I will explain how learning can be rigorously interpreted as a form of information processing and then explore the evidence for whether learning also takes place in organismal contexts outside the brain, such as physiology, development, and individual cells. I will try to explain why it is important to build bridges in this way between cognitive science and systems biology, why concepts and methods from various branches of engineering may be helpful in this task, and what the eventual impact may be on how we think about the organism.

Co-Creation: Systems Thinking Beyond the Machine

Complexity thinking is all the rage — in the arts and sciences. Yet, there are two different strands of thinking about complexity, which are often confounded. The first comes from cybernetics, focussing on control in complex situations. The second is ecological, aiming at sustainable participation in a reality beyond control. Their difference rests on a fundamental distinction: is complexity rooted in feedback regulation or collective co-creation? While feedback remains mechanistic, co-creation generates new spaces of possibilities. We need it to understand life and its evolution. And it empowers us to rewrite our future, to escape our mechanistic cage without abandoning scientific rigor. In this paper, we illustrate how we implement these powerful yet abstract principles through our artistic and philosophical practice.

Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds

Synthetic biology and bioengineering provide the opportunity to create novel embodied cognitive systems (otherwise known as minds) in a very wide variety of chimeric architectures combining evolved and designed material and software. These advances are disrupting familiar concepts in the philosophy of mind, and require new ways of thinking about and comparing truly diverse intelligences, whose composition and origin are not like any of the available natural model species. In this Perspective, I introduce TAME-Technological Approach to Mind Everywhere-a framework for understanding and manipulating cognition in unconventional substrates. TAME formalizes a non-binary (continuous), empirically-based approach to strongly embodied agency. TAME provides a natural way to think about animal sentience as an instance of collective intelligence of cell groups, arising from dynamics that manifest in similar ways in numerous other substrates. When applied to regenerating/developmental systems, TAME suggests a perspective on morphogenesis as an example of basal cognition. The deep symmetry between problem-solving in anatomical, physiological, transcriptional, and 3D (traditional behavioral) spaces drives specific hypotheses by which cognitive capacities can increase during evolution. An important medium exploited by evolution for joining active subunits into greater agents is developmental bioelectricity, implemented by pre-neural use of ion channels and gap junctions to scale up cell-level feedback loops into anatomical homeostasis. This architecture of multi-scale competency of biological systems has important implications for plasticity of bodies and minds, greatly potentiating evolvability. Considering classical and recent data from the perspectives of computational science, evolutionary biology, and basal cognition, reveals a rich research program with many implications for cognitive science, evolutionary biology, regenerative medicine, and artificial intelligence.

Cellosophy

Cognition and Intelligence in Unicellular Creatures

Cognition all the way down 2.0: neuroscience beyond neurons in the diverse intelligence era

This paper formalizes biological intelligence as search efficiency in multi-scale problem spaces, aiming to resolve epistemic deadlocks in the basal “cognition wars” unfolding in the Diverse Intelligence research program. It extends classical work on symbolic problem-solving to define a novel problem space lexicon and search efficiency metric. Construed as an operationalization of intelligence, this metric is the decimal logarithm of the ratio between the cost of a random walk and that of a biological agent. Thus, the search efficiency measures how many orders of magnitude of dissipative work an agentic policy saves relative to a maximal-entropy search strategy. Empirical models for amoeboid chemotaxis and barium-induced planarian head regeneration show that, under conservative (i.e., intelligence-underestimating) assumptions, even ‘simple’ organisms are from two-hundred- to sextillion-fold more efficient in problem space exploration. In this sense, the deep insights of neuroscience are not about neurons per se, but about the policies and patterns of physics and mathematics that function as a kind of “cognitive glue” binding parts toward higher levels of collective intelligence in wholes of highly diverse composition and origin. Therefore, our synthesis argues that the “mark of the cognitive” is perhaps better sought in the measurable efficiency with which living systems, from single cells to complex organisms, traverse energy and information gradients to tame combinatorial explosions-one problem space at a time.

Invisible Designers: Brain Evolution Through the Lens of Parasite Manipulation

AbstractThe ability of parasites to manipulate host behavior to their advantage has been studied extensively, but the impact of parasite manipulation on the evolution of neural and endocrine mechanisms has remained virtually unexplored. If selection for countermeasures has shaped the evolution of nervous systems, many aspects of neural functioning are likely to remain poorly understood until parasites—the brain’s invisible designers—are included in the picture. This article offers the first systematic discussion of brain evolution in light of parasite manipulation. After reviewing the strategies and mechanisms employed by parasites, the paper presents a taxonomy of host countermeasures with four main categories, namely: restrict access to the brain; increase the costs of manipulation; increase the complexity of signals; and increase robustness. For each category, possible examples of countermeasures are explored, and the likely evolutionary responses by parasites are considered. The article then discusses the metabolic, computational, and ecological constraints that limit the evolution of countermeasures. The final sections offer suggestions for future research and consider some implications for basic neuroscience and psychopharmacology. The paper aims to present a novel perspective on brain evolution, chart a provisional way forward, and stimulate research across the relevant disciplines.

AI That Evolves in the Wild | Edge.org

I’m interested not in domesticated AI—the stuff that people are trying to sell. I'm interested in wild AI—AI that evolves in the wild. I’m a naturalist, so that’s the interesting thing to me. Thirty-four years ago there was a meeting just like this in which Stanislaw Ulam said to everybody in the room—they’re all mathematicians—"What makes you so sure that mathematical logic corresponds to the way we think?" It’s a higher-level symptom. It’s not how the brain works. All those guys knew fully well that the brain was not fundamentally logical.

Principles of Minimal Cognition: Casting Cognition as Sensorimotor Coordination

Within the cognitive sciences, cognition tends to be interpreted from an anthropocentric perspective, involving a stringent set of human capabilities. Instead, we suggest that cognition is better explicated as a much more general biological phenomenon, allowing the lower bound of cognition to extend much further down the phylogenetic scale. We argue that elementary forms of cognition can already be witnessed in prokaryotes possessing a functional sensorimotor analogue of the nervous system. Building on a case-study of the Escherichia coli bacterium and its sensorimotor system, the TCST-system, we home in on the characteristics of minimal cognition, and distinguish it from more basic forms of ontogenetic adaptation. In our view, minimal cognition requires an embodiment consisting of a sensorimotor coupling mechanism that subsumes an autopoietic organization; this forms the basis of the growing consensus that the core of cognition revolves around sensorimotor coupling. We discuss the relevance of our interpretation of minimal cognition for the study of cognition in general

Stigmergic Collaboration: A Theoretical Framework for Mass Collaboration

"This thesis presents an application-oriented theoretical framework for generalised and specific collaborative contexts with a special focus on Internet-based mass collaboration. The proposed framework is informed by the author's many years of collaborative arts practice and the design, building and moderation of a number of online collaborative environments across a wide range of contexts and applications. The thesis provides transdisciplinary architecture for describing the underlying mechanisms that have enabled the emergence of mass collaboration and other activities associated with 'Web 2.0' by incorporating a collaboratively developed definition and general framework for collaboration and collective activity, as well as theories of swarm intelligence, stigmergy, and distributed cognition. "Accompanying this creative arts thesis is a DVD-Rom which includes offline versions of the three Internet based collaborative environments designed, built and implemented in accordance with the frameworks for digital stigmergy and mass collaboration developed in the written work. The creative works in conjunction with the written thesis help to explore and more rigorously define the collaborative process in general, while testing the theory that stigmergy is an inherent component of collaborative processes which incorporate collective material production. "Supported by a range of contemporary examples of Internet activity, including the accompanying creative works, it is found that stigmergy is a deeply rooted mechanism inherent in not only traditional material collaborative processes, but a range of emerging online practices which may be broadly categorised as digital stigmergic cooperation and collaboration. This latter class enables the extreme scaling seen in mass collaborative projects such as Wikipedia.org, open source software projects and the massive, multiplayer environment, Second Life. This scaling is achieved through a range of attributes which are examined, such as the provision of a localised site of individualistic engagement which reduces demands placed upon participants by the social negotiation of contributions while increasing capacity for direct and immediate creative participation via digital workspaces. Also examined are a range of cultural, economic and sociopolitical impacts which emerge as a direct result of mass collaboration's highly distributed, non-market based, peer-production processes, all of which are shown to have important implications for the further transformation of our contemporary information and media landscape."

Towards Post-Interaction Computing: Addressing Immediacy, (un)Intentionality, Instability and Interaction Effects

We situate the debate on intentionality within the rise of cognitive neuroscience and argue that cognitive neuroscience can explain intentionality. We discuss the explanatory significance of ascribing intentionality to representations. At first, we ...