Human Simulation and Sustainability : Ontological, Epistemological, and Ethical Reflections

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Norm-Establishing and Norm-Following in Autonomous Agency

Living agency is subject to a normative dimension (good-bad, adaptive-maladaptive) that is absent from other types of interaction. We review current and historical attempts to naturalize normativity from an organism-centered perspective, identifying two central problems and their solution: (1) How to define the topology of the viability space so as to include a sense of gradation that permits reversible failure, and (2) how to relate both the processes that establish norms and those that result in norm-following behavior. We present a minimal metabolic system that is coupled to a gradient-climbing chemotactic mechanism. Studying the relationship between metabolic dynamics and environmental resource conditions, we identify an emergent viable region and a precarious region where the system tends to die unless environmental conditions change. We introduce the concept of normative field as the change of environmental conditions required to bring the system back to its viable region. Norm-following, or normative action, is defined as the course of behavior whose effect is positively correlated with the normative field. We close with a discussion of the limitations and extensions of our model and some final reflections on the nature of norms and teleology in agency

Human Simulation and Sustainability: Ontological, Epistemological, and Ethical Reflections

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Ontological framework to improve motion planning of manipulative agents through semantic knowledge-based reasoning

This paper describes the actions taken in developing a framework that aims to improve the motion planning of a manipulative robotic agent through reasoning based on semantic knowledge. The Semantic Web Rule Language (SWRL) was employed to draw new insights from the existing information about the robotic system and its environment. Recent ontology-based standards have been developed (IEEE 1872-2015; IEEE 1872.2-2021; IEEE 7007-2021), and others are currently under development (IEEE P1872.1; IEEE P1872.3) to improve robot performance in task execution. Ontological knowledge “semantic map" was generated using a deep neural network trained to detect and classify objects in the environment where the manipulator agent acts. Manipulation constraints were deduced, and the environment corresponding to the agent’s manipulation workspace was created so the planner could interpret it to generate a collision-free path. Several SPARQL queries were used to explore the semantic map and allow ontological reasoning. The proposed framework was implemented and validated in a real experimental setting, using the ROSPlan planning framework to perform the planning tasks. This ontology-based framework proved to be a promising strategy. E.g., it allows the robotic manipulative agent to interact with objects, e.g., to choose a mobile phone or a water bottle, using semantic information from the environment to solve the requested tasks.This work is financed by national funds through FCT - Foundation for Science and Technology, I.P., through IDMEC, under LAETA, project UIDB/50022/2020. The work of Rodrigo Bernardo was supported by the PhD Scholarship BD/6841/2020 from FCT. This work has received funding from: the project 0770_EUROAGE2_4_E (POCTEP Programa Interreg V-A Spain-Portugal), and the European Union’s Horizon 2020 programme under StandICT.eu 2023 (under Grant Agreement No.: 951972).info:eu-repo/semantics/publishedVersio

Developmental Systems Theory as a Process Theory

Griffiths and Russell D. Gray (1994, 1997, 2001) have argued that the fundamental unit of analysis in developmental systems theory should be a process – the life cycle – and not a set of developmental resources and interactions between those resources. The key concepts of developmental systems theory, epigenesis and developmental dynamics, both also suggest a process view of the units of development. This chapter explores in more depth the features of developmental systems theory that favour treating processes as fundamental in biology and examines the continuity between developmental systems theory and ideas about process in the work of several major figures in early 20th century biology, most notable C.H Waddington

Emerging in the Image of God: From Evolution to Ethics in a Second Naïveté Understanding of Christian Anthropology

Through a careful integration of theological, philosophical, and the natural scientific sources, the biblical concepts of the image of God and the knowledge of good and evil have the potential to remain important and appropriate descriptors of the human condition, including the possibility and necessity of human morality. This study employs French philosopher Paul Ricoeur\u27s notion of second naïveté understanding to demonstrate the hermeneutical significance of contemporary biocultural evolutionary theory for reinterpreting and reappropriating these ancient symbols of Christian anthropology as terms equipped to encapsulate a morally fruitful and intellectually honest conceptual framework for constructing, conducting, and evaluating theological anthropology and ethics today. Forging and polishing this hermeneutical lens for the purpose of recasting a biblically-based picture of humanity involves alloying these ancient concepts with others from the interrelated fields of cognitive linguistics, evolutionary psychology, and emergence. Viewed through this lens, the dissertationing chapters of Genesis describe human beings as creatures wrought of the creation and embedded within it to the same extent as all other creatures. Though ordinary in every other aspect, human creatures are unique in that they have emerged with an ambivalent condition of freedom through which they bear the vocation to re-present the creative beneficence of the God who shares power and does not create through violence. I defend this thesis in seven chapters. In the first chapter, I introduce the research topic, goals, and hermeneutical procedure for this study. Chapters 2 and 3 describe biocultural evolution and evolutionary psychology within a non-reductive emergentist perspective as sources and resources for contemporary theological anthropology. In chapter 4, I propose an articulation of the doctrine of the imago Dei within this evolutionary worldview. Chapter 5 situates the knowledge of good and evil vis-à-vis biocultural evolution and recent biblical studies. I then construct a proposal in chapter 6 for how this second naïveté understanding of the image of God and the knowledge of good and evil dissertations up new frameworks and frontiers for fundamental theological ethics. Finally, chapter 7 offers a summative and prospective conclusion to this study and its likely impact on my future research

Can Science Explain Consciousness?

For diverse reasons, the problem of phenomenal consciousness is persistently challenging. Mental terms are characteristically ambiguous, researchers have philosophical biases, secondary qualities are excluded from objective description, and philosophers love to argue. Adhering to a regime of efficient causes and third-person descriptions, science as it has been defined has no place for subjectivity or teleology. A solution to the “hard problem” of consciousness will require a radical approach: to take the point of view of the cognitive system itself. To facilitate this approach, a concept of agency is introduced along with a different understanding of intentionality. Following this approach reveals that the autopoietic cognitive system constructs phenomenality through acts of fiat, which underlie perceptual completion effects and “filling in”—and, by implication, phenomenology in general. It creates phenomenality much as we create meaning in language, through the use of symbols that it assigns meaning in the context of an embodied evolutionary history that is the source of valuation upon which meaning depends. Phenomenality is a virtual representation to itself by an executive agent (the conscious self) tasked with monitoring the state of the organism and its environment, planning future action, and coordinating various sub- agencies. Consciousness is not epiphenomenal, but serves a function for higher organisms that is distinct from that of unconscious processing. While a strictly scientific solution to the hard problem is not possible for a science that excludes the subjectivity it seeks to explain, there is hope to at least psychologically bridge the explanatory gulf between mind and matter, and perhaps hope for a broader definition of science

Transcriptomics of learning

Learning is a basic and important component of behavior yet we have very little empirical information about the interaction between mechanisms of learning and evolution. In our work, we are testing hypotheses about the neurogenetic mechanisms through which animal learning abilities evolve. We are able to test this directly by using experimentally evolved populations of flies, which differ in learning ability. These populations were previously evolved within the lab by creating worlds with different patterns of change following theoretically predicted effects on which enhanced learning will evolve. How has evolution acted to modulate genes and gene expression in the brain to accomplish the behavioral differences observed in these populations? We report results from work characterizing the differences in gene expression in the brains of populations of Drosophila that evolved in environments favoring learning from paired populations evolving under control conditions. Using olfactory conditioning in the t-maze, we first show that flies which evolved enhanced learning in an oviposition context also have a generalized enhanced learning ability. We dissected brains from flies following experience learning in the tmaze and analyzed pooled samples using RNAseq. We completed a factorial design of comparing the brains of flies from high learning populations with control populations and in each of two conditions: after conditioning and without conditioning. Following differential gene expression analysis, we found differences within known suites of genes as well as novel transcripts. We have also found evidence of predicted trade-offs between immune response and cognitive capacity. We present these data, as well as results from gene ontology analyses. Combining predictions from behavioral ecology with experimental evolution is a powerful approach to assessing the suites of genetic and neurological changes associated with the evolution of complex behavioral traits, like learning. By analyzing the genomic mechanisms of what has evolved under experimental conditions, we can make a great step forward in understanding the evolution of learning and of plasticity in general