In his article on The Liabilities of Mobility, Merker asserts that “Consciousness presents us with a stable arena for our actions—the world …” and argues for this property as providing evolutionary pressure for the evolution of consciousness. In this commentary, I will explore the implications of Merker’s ideas for consciousness in artificial agents as well as animals, and also meet some possible objections to his evolutionary pressure claim.

In his article on The Liabilities of Mobility, Merker asserts that “Consciousness presents us with a stable arena for our actions—the world …” and argues for this property as providing evolutionary pressure for the evolution of consciousness. In this commentary, I will explore the implications of Merker’s ideas for consciousness in artificial agents as well as animals, and also meet some possible objections to his evolutionary pressure claim.

The idea that we might be robots is no longer the stuff of science fiction; decades of research in evolutionary biology and cognitive science have led many esteemed scientists to the conclusion that, according to the precepts of universal Darwinism, humans are merely the hosts for two replicators that have no interest in us except as conduits for replication. Richard Dawkins, for example, jolted us into realizing that we are just survival mechanisms for our own genes, sophisticated robots in (...) service of huge colonies of replicators to whom concepts of rationality, intelligence, agency, and even the human soul are irrelevant. Accepting and now forcefully responding to this decentering and disturbing idea, Keith Stanovich here provides the tools for the "robot's rebellion," a program of cognitive reform necessary to advance human interests over the limited interest of the replicators and define our own autonomous goals as individual human beings. He shows how concepts of rational thinking from cognitive science interact with the logic of evolution to create opportunities for humans to structure their behavior to serve their own ends. These evaluative activities of the brain, he argues, fulfill the need that we have to ascribe significance to human life. We may well be robots, but we are the only robots who have discovered that fact. Only by recognizing ourselves as such, argues Stanovich, can we begin to construct a concept of self based on what is truly singular about humans: that they gain control of their lives in a way unique among life forms on Earth—through rational self-determination. (shrink)

Robot enthusiasts envision robots will become a “race unto themselves” as they cohabit with the humankind one day. Profound questions arise surrounding one of the major areas of research in the contemporary world—that concerning artificial intelligence. Fascination and anxiety that androids impose upon us hinges on how we come to conceive of the “Cultural Other.” Applying the notion of the “other” in multicultural research process, we will explore how the “Other” has been used to illustrate values and theories about robots, (...) as a mirror for the self. In this paper, we focus on the social, cultural, and religious implications of humans’ attitudes toward relationships between humans with robots. Six major views on humanoid robots are proposed: (1) robots as the “Frightening Other,” (2) robots as the “Subhuman Other,” (3) robots as the “Human Substitute,” (4) robots as the “Sentient Other,” (5) robots as the “Divine Other,” and (6) robots as the “Co-evolutionary Path to Immortality.” The likely and preferable scenario is the last one, which is compatible with an optimistic posthuman world in our evolutionary future. We imagine whether humans will meet the challenge of loving all living and non-living beings (including mechanical entities) might be the key to the co-evolution of both species and the ultimate happiness. (shrink)

Machines will attain human levels of intelligence by the year 2040, predicts robotics expert Hans Moravec. And by 2050, they will have far surpassed us. In this mind-bending new book, Hans Moravec takes the reader on a roller coaster ride packed with such startling predictions. He tells us, for instance, that in the not-too-distant future, an army of robots will displace workers, causing massive, unprecedented unemployment. But then, says Moravec, a period of very comfortable existence will follow, as humans (...) benefit from a fully automated economy. And eventually, as machines evolve far beyond humanity, robots will supplant us. But if Moravec predicts the end of the domination by human beings, his is not a bleak vision. Far from railing against a future in which machines rule the world, Moravec embraces it, taking the startling view that intelligent robots will actually be our evolutionary heirs. "Intelligent machines, which will grow from us, learn our skills, and share our goals and values, can be viewed as children of our minds." And since they are our children, we will want them to outdistance us. In fact, in a bid for immortality, many of our descendants will choose to transform into "ex humans," as they upload themselves into advanced computers. We will become our children and live forever. In his provocative new book, the highly anticipated follow-up to his bestselling volume Mind Children, Moravec charts the trajectory of robotics in breathtaking detail. A must read for artificial intelligence, technology, and computer enthusiasts, Moravec's freewheeling but informed speculations present a future far different than we ever dared imagine. (shrink)

Responds to the idea that humans are merely survival mechanisms for their own genes, providing the tools to advance human interests over the interests of the replicators through rational self-determination.

Among ethicists and engineers within robotics there is an ongoing discussion as to whether ethical robots are possible or even desirable. We answer both of these questions in the positive, based on an extensive literature study of existing arguments. Our contribution consists in bringing together and reinterpreting pieces of information from a variety of sources. One of the conclusions drawn is that artifactual morality must come in degrees and depend on the level of agency, autonomy and intelligence of the (...) machine. Moral concerns for agents such as intelligent search machines are relatively simple, while highly intelligent and autonomous artifacts with significant impact and complex modes of agency must be equipped with more advanced ethical capabilities. Systems like cognitive robots are being developed that are expected to become part of our everyday lives in future decades. Thus, it is necessary to ensure that their behaviour is adequate. In an analogy with artificial intelligence, which is the ability of a machine to perform activities that would require intelligence in humans, artificial morality is considered to be the ability of a machine to perform activities that would require morality in humans. The capacity for artificial (artifactual) morality, such as artifactual agency, artifactual responsibility, artificial intentions, artificial (synthetic) emotions, etc., come in varying degrees and depend on the type of agent. As an illustration, we address the assurance of safety in modern High Reliability Organizations through responsibility distribution. In the same way that the concept of agency is generalized in the case of artificial agents, the concept of moral agency, including responsibility, is generalized too. We propose to look at artificial moral agents as having functional responsibilities within a network of distributed responsibilities in a socio-technological system. This does not take away the responsibilities of the other stakeholders in the system, but facilitates an understanding and regulation of such networks. It should be pointed out that the process of development must assume an evolutionary form with a number of iterations because the emergent properties of artifacts must be tested in real world situations with agents of increasing intelligence and moral competence. We see this paper as a contribution to the macro-level Requirement Engineering through discussion and analysis of general requirements for design of ethical robots. (shrink)

This chapter contains sections titled: Can a Material Thing Think? Tooley's Reply to the Evolutionary Argument against Naturalism.

The study of imitation and other mechanisms of social learning is an exciting area of research for all those interested in understanding the origin and the nature of animal learning in a social context. Moreover, imitation is an increasingly important research topic in Artificial Intelligence and social robotics which opens up the possibility of individualized social intelligence in robots that are part of a community, and allows us to harness not only individual learning by the single robot, but also (...) the acquisition of new skills by observing other members of the community. After an introduction to the main research issues in research on imitation in various fields, we motivate the particular focus of this work, namely the correspondence problem. We describe Action Learning for Imitation via Correspondences between Embodiments, an implemented generic framework for solving the correspondence problem between differently embodied robots. Alice enables a robotic agent to learn a behavioral repertoire suitable to performing a task by observing a model agent. Importantly, the model agent could possibly possess a different type of body, e.g. a different number of limbs or joints, a different height, different sensors, a different basic action repertoire, etc. Previously, in a test-bed where the agents differed according to their possible movement patterns, we demonstrated that the character of imitation achieved will depend on the granularity of subgoal matching, and on the metrics used to evaluate success. In our current work, we implemented Alice in a new test-bed called Rabit where simple simulated robotic arm agents use various metrics for evaluating success according to actions, states, effects, or weighted combinations. We examine the roles of synchronization, looseness of perceptual matching, and of proprioceptive matching by a series of experiments. Also, we study how Alice copes with changes in the embodiment of the imitator during learning. Our simulation results suggest that synchronization and loose perceptual matching allow for faster acquisition of behavioral compentencies at low error rates. Social learning plays a role as a replication mechanism for behaviors and results in variability when the transmitted behavior differs from the model’s behavior, thus providing the evolutionary substrate for culture and its pre-cursors. Social learning in robotics could therefore serve as the basis for culture in societies whose members include artificial agents. We address the use of imitative social learning mechanisms like Alice for transmission of skills between robots, and give first examples of transmission of a skill despite differences in embodiment of agents involved. In the particular setup, transmission occurs through a chain, as well as emerging in cyclic arrangements of robots. These simple examples demonstrate that by using social learning and imitation, cultural transmission is possible among robots, even in heterogeneous groups of robots. (shrink)

As the artificial intelligence of computers grows ever-more sophisticated and continues to surpass the capacities of human minds in many ways, people are forced to question alleged ontological categories that separate humans from machines. As we are entering the world which is populated by non-enhanced and enhanced humans, cyborgs, robots, androids, avatars, and clones among them, the desire for evolutionary mastery of the natural world has taken on the two main directions: merging with machines in disembodied forms or embodied (...) forms. As a path to breaking past the discontinuity between humans and machines and enter into a world beyond the “fourth” discontinuity, machines are viewed as an evolutionary step toward the “perfection” or “immortality” of humans. However, this popular, instrumental views of machines, stemming from the existential death anxiety and the hope for transcending mortality, reveals the karmic dilemma of desiring or grasping something. We shall discuss the possibility that machines can present, ultimately, a revolutionary step rather than an evolutionary step toward understanding “who we are.” The path toward a continuity with machines lies not in our desire for merging with the robots, but in recognizing the arbitrary nature of all such identity categories. This radical understanding of the self-identity can be seen as a facet of enlightened experience. (shrink)

A formalism is developed that treats a robot as a subject that can interpret its own experience rather than an object that is interpreted within our experience. A regulative definition of a meaningful experience in robots is proposed in which the present sensible experience is considered meaningful to the agent, as the subject of the experience, if it can be related to the agent's temporal horizons. This definition is validated by demonstrating that such an experience in evolutionary autonomous agents (...) is embodied, contextual and normative, as is required for the maintenance of phenomenological accuracy. With this formalism it is shown how a dialectic similar to that described in Hegelian phenomenology can emerge in the robotic experience and why the presence of such a dialectic can serve as a constraint in the further development of cognitive agents. (shrink)

The currently leading cognitive theory of consciousness, Global Workspace Theory,1,2 postulates that the primary functions of consciousness include a global broadcast serving to recruit internal resources with which to deal with the current situation and to modulate several types of learning. In addition, conscious experiences present current conditions and problems to a "self" system, an executive interpreter that is identifiable with brain structures like the frontal lobes and precuneus.1Be it human, animal or artificial, an autonomous agent3 is said to be (...) functionally conscious if its control structure (mind) implements Global Workspace Theory and the LIDA Cognitive Cycle, which includes unconscious memory and control functions needed to integrate the conscious component of the system. We would therefore consider humans, many animals4 and even some virtual or robotic agents5,6 to be functionally conscious. Such entities may approach phenomenal consciousness, as found in human and other biological brains, as additional brain-like features are added.Here we argue that adding mechanisms to produce a stable, coherent perceptual field7 in a LIDA controlled mobile robot might provide a small but significant step toward phenomenal consciousness in machines.>8 We also propose that implementing several of the various notions of self in such a LIDA controlled robot may well prove another step toward phenomenal consciousness in machines. (shrink)

In multiple robot systems, the problem of allocation of complex tasks to heterogeneous teams of robots, also known as the multiple robot coalition formation problem, has begun to receive considerable attention. Efforts to address the problem range from heuristics based approaches that search the subspaces of the coalition structure to evolutionary learning approaches. Conventional approaches typically strive to optimize a single objective function such as the number of tasks executed or the time required to execute all tasks, or a (...) weighted function of such objectives. In real world applications, objectives such as minimizing distance traveled and maximizing the number of tasks completed are often conflicting in nature. The coalition formation problem thus naturally lends itself to a multi-objective optimization approach based on evolutionary learning. In this paper, we formulate the problem of mapping coalitions of robots to a set of tasks as a multi-objective optimization problem and propose a variant of non-dominated sorting genetic algorithm to arrive at trade-off solutions. Additionally, we extend the solution to domains where robot resources are non-additive. Simulations demonstrate the efficacy of the proposed approach in generating the set of Pareto-optimal solutions. (shrink)

Robots are widely expected—and pushed—to transform open-field agriculture, but these visions remain wedded to optimizing monocultural farming systems. Meanwhile there is little pull for automation from ecology-based, diversified farming realms. Noting this gap, we here explore the potential for robots to foster an agroecological approach to crop production. The research was situated in The Netherlands within the case of _pixel cropping_, a nascent farming method in which multiple food and service crops are planted together in diverse assemblages employing agroecological practices (...) such as intercropping and biological pest control. Around this case we engaged with a variety of specialists in discussion groups, workshops, and design challenges to explore the potential of field robots to meet the multifaceted demands of highly diverse agroecological cropping systems. This generated a spectrum of imaginations for how automated tools might—or might not—be appropriately used, ranging from fully automated visions, to collaborative scenarios, to fully analogue prototypes. We found that automating agroecological cropping systems requires finding ways to imbue the ethos of agroecology into designed tools, thereby seeking to overcome tensions between production aims and other forms of social and ecological care. We conclude that a rethinking of automation is necessary for agroecological contexts: not as a blueprint for replacing humans, but making room for analogue and hybrid forms of agricultural work. These findings highlight a need for design processes which include a diversity of actors, involve iterative design cycles, and incorporate feedback between designers, practitioners, tools, and cropping systems. (shrink)

This special issue of ‘Sophia’ aims to reflect upon future evolutions of religions and their related narratives and imaginaries from a critical and generative understanding of our ancient sources. Bodies are locations of creative power and symbolic proliferation. Cyborgian, transhuman, and posthuman embodiments are going to generate visions of the divine in tune with such an epistemic shift, by addressing questions such as: can God be represented as a cyborg? Could robots and avatars be prophets? Is internet a suitable setting (...) for a posthuman theophany? This special issue articulates within the frame of a relational ontological perspective, according to which the notion of the divine evolves, as much as human and non-human persons do. In this evolutionary scenario, the representation of the divine realm may shift from era to era, adapting to new natural-cultural formations. This special issue argues that the posthuman paradigm shift will be followed by a symbolic turn in religious imaginaries as well. (shrink)

Ethical concerns regarding agricultural practices can be found to co-evolve with technological developments. This paper aims to create an understanding of ethics that is helpful in debating technological innovation by studying such a co-evolution process in detail: the development and adoption of the milking robot. Over the last decade an increasing number of milking robots, or automatic milking systems (AMS), has been adopted, especially in the Netherlands and a few other Western European countries. The appraisal of this new technology in (...) ethical terms has appeared to be a complicated matter. Compared to using a conventional milking parlor, the use of an AMS entails in several respects a different practice of dairy farming, the ethical implications and evaluation of which are not self-evident but are themselves part of a dynamic process. It has become clear that with its use, the entire practice of dairy farming has been reorganized around this new device. With a robot, cows must voluntarily present themselves to be milked, whereby an ethical norm of (individual) freedom for cows can be seen to emerge together with this new technology. But adopting a robot also implies changes in what is considered to be a good farmer and an appropriate relation between farmer and cow. Through interviews, attending “farmers’ network” meetings in the Netherlands, and studying professional literature and dedicated dairy farming web forums, this paper traces the way that ethical concerns are a dynamic part of this process of rearranging a variety of elements of the practice of dairy farming. (shrink)

The concept of adaptation is employed in many fields such as biology, psychology, cognitive sciences, robotics, social sciences, even literacy and art,1 and its meaning varies quite evidently according to the particular research context in which it is applied. We expect to find a particularly rich catalogue of meanings within evolutionary biology, where adaptation has held a particularly central role since Darwin’s The Origin of Species (1859) throughout important epistemological shifts and scientific findings that enriched and diversified the (...) concept. Accordingly, a conceptual taxonomy of adaptation in evolutionary biology may help to disambiguate it. Interdisciplinary researches focused on adaptation would benefit from such a result. In the present work we recognize and define seven different meanings of adaptation: (1) individual fitness; (2) adaptation of a population; (3) adaptation as the process of natural selection; (4) adaptive traits; (5) molecular adaptation; (6) adaptation as structural tinkering; (7) plasticity. For convenience here, we refer to them as W-, P-, NS-, T-, M-, S- and PL-ADAPTATION. We present the seven meanings in some detail, hinting at their respective origins and conceptual developments in the history of evolutionary thought (references are offered for further deepening). However, it is important to point out that evolution researchers seldom if ever refer to a single meaning purified from the others. This applies also to the authors we cite as representatives of one of the seven meanings. In Discussion and Conclusion draw from our work some future perspectives for adaptation within evolutionary biology. (shrink)

Physical and emotional intimacy between humans and robots may become commonplace over the next decades, as technology improves at a rapid rate. This development provides new questions pertaining to how people perceive robots designed for different kinds of intimacy, both as companions and potentially as competitors. We performed an randomized experiment where participants read of either a robot that could only perform sexual acts, or only engage in non-sexual platonic love relationships. The results of the current study show that females (...) have less positive views of robots, and especially of sex robots, compared to men. Contrary to the expectation rooted in evolutionary psychology, females expected to feel more jealousy if their partner got a sex robot, rather than a platonic love robot. The results further suggests that people project their own feelings about robots onto their partner, erroneously expecting their partner to react as they would to the thought of ones’ partner having a robot. (shrink)

Our main hypothesis is that an extended moral agent cannot fulfill their expectation of “extendedness” without a dynamical and evolutionary ecosystem where the agent develops and behave properly. It is important to establish a bridge between extended moral agents and ecosystems for two reasons: first, because there is not an enough direct theoretical reflection about this link. The scholars focus has been independently in improving the “extended agent theory”, the concepts of “ecosystem” or “ecosystem of innovation”. Second, if we (...) want to understand the wide scope of the decentered ethics in design of mobile robots and AI these two theoretical frames cannot be seen separately but in join interdependency. (shrink)

In considering how to best deploy robotic systems in public and private sectors, we must consider what individuals will expect from the robots with which they interact. Public awareness of robotics—as both military machines and domestic helpers—emerges out of a braided stream composed of science fiction and popular science. These two genres influence news media, government and corporate spending, and public expectations. In the Euro-American West, both science fiction and popular science are ambivalent about the military applications for (...) class='Hi'>robotics, and thus we can expect their readers to fear the dangers posed by advanced robotics while still eagerly anticipating the benefits to be accrued through them. The chief pop science authors in robotics and artificial intelligence have a decidedly apocalyptic bent and have thus been described as leaders in a social movement called "Apocalyptic AI." In one form or another, such authors look forward to a transcendent future in which machine life succeeds human life, thanks to the march of evolutionary progress. The apocalyptic promises of popular robotics presume that presently exponential growth in computing will continue indefinitely, producing a "Singularity." During the Singularity, technological progress will be so rapid that undreamt of changes will take place on earth, the most important of which will be the evolutionary succession of human beings by massively intelligent robots and the "uploading" of human consciousness into computer bodies. This supposedly inevitable transition into post-biological life looms across the entire scope of pop robotics and artificial intelligence, and it is from beneath that shadow that all popular books engage the military and the ethics of warfare. Creating a just future will require that we transcend the apocalyptic discourse of pop science and establish an ethical approach to researching and deploying robots, one that emphasizes human rather than robot welfare; doing so will require the collaboration of social scientists, humanists, and scientists. (shrink)

Modern cognitive science cannot be understood without recent developments in computer science, artificial intelligence, robotics, neuroscience, biology, linguistics, and psychology. Classic analytic philosophy as well as traditional AI assumed that all kinds of knowledge must eplicitly be represented by formal or programming languages. This assumption is in contradiction to recent insights into the biology of evolution and developmental psychology of the human organism. Most of our knowledge is implicit and unconscious. It is not formally represented, but embodied knowledge which (...) is learnt by doing and understood by bodily interacting with ecological niches and social environments. That is true not only for low-level skills, but even for high-level domains of categorization, language, and abstract thinking. Embodied cognitive science, AI, and robotics try to build the embodied mind in an artificial evolution. From a philosophical point of view, it is amazing that the new ideas of embodied mind and robotics have deep roots in 20th-century philosophy. (shrink)

The philosophical conception of mechanistic explanation is grounded on a limited number of canonical examples. These examples provide an overly narrow view of contemporary scientific practice, because they do not reflect the extent to which the heuristic strategies and descriptive practices that contribute to mechanistic explanation have evolved beyond the well-known methods of decomposition, localization, and pictorial representation. Recent examples from evolutionary robotics and network approaches to biology and neuroscience demonstrate the increasingly important role played by computer simulations (...) and mathematical representations in the epistemic practices of mechanism discovery and mechanism description. These examples also indicate that the scope of mechanistic explanation must be re-examined: With new and increasingly powerful methods of discovery and description comes the possibility of describing mechanisms far more complex than traditionally assumed. (shrink)

Since the early eighties, computationalism in the study of the mind has been “under attack” by several critics of the so-called “classic” or “symbolic” approaches in AI and cognitive science. Computationalism was generically identified with such approaches. For example, it was identified with both Allen Newell and Herbert Simon’s Physical Symbol System Hypothesis and Jerry Fodor’s theory of Language of Thought, usually without taking into account the fact ,that such approaches are very different as to their methods and aims. Zenon (...) Pylyshyn, in his influential book Computation and Cognition, claimed that both Newell and Fodor deeply influenced his ideas on cognition as computation. This probably added to the confusion, as many people still consider Pylyshyn’s book as paradigmatic of the computational approach in the study of the mind. Since then, cognitive scientists, AI researchers and also philosophers of the mind have been asked to take sides on different “paradigms” that have from time to time been proposed as opponents of (classic or symbolic) computationalism. Examples of such oppositions are: -/- computationalism vs. connectionism, computationalism vs. dynamical systems, computationalism vs. situated and embodied cognition, computationalism vs. behavioural and evolutionary robotics. -/- Our preliminary claim in section 1 is that computationalism should not be identified with what we would call the “paradigm (based on the metaphor) of the computer” (in the following, PoC). PoC is the (rather vague) statement that the mind functions “as a digital computer”. Actually, PoC is a restrictive version of computationalism, and nobody ever seriously upheld it, except in some rough versions of the computational approach and in some popular discussions about it. Usually, PoC is used as a straw man in many arguments against computationalism. In section 1 we look in some detail at PoC’s claims and argue that computationalism cannot be identified with PoC. In section 2 we point out that certain anticomputationalist arguments are based on this misleading identification. In section 3 we suggest that the view of the levels of explanation proposed by David Marr could clarify certain points of the debate on computationalism. In section 4 we touch on a controversial issue, namely the possibility of developing a notion of analog computation, similar to the notion of digital computation. A short conclusion follows in section 5. (shrink)

We argue that progress in our scientific understanding of the `social mind' is hampered by a number of unfounded assumptions. We single out the widely shared assumption that social behavior depends solely on the capacities of an individual agent. In contrast, both developmental and phenomenological studies suggest that the personal-level capacity for detached `social cognition' (conceived as a process of theorizing about and/or simulating another mind) is a secondary achievement that is dependent on more immediate processes of embodied social interaction. (...) We draw on the enactive approach to cognitive science to further clarify this strong notion of `social interaction' in theoretical terms. In addition, we indicate how this interaction theory (IT) could eventually be formalized with the help of a dynamical systems perspective on the interaction process, especially by making use of evolutionary robotics modeling. We conclude that bringing together the methods and insights of developmental, phenomenological, enactive and dynamical approaches to social interaction can provide a promising framework for future research. Keywords: theory of mind; cognitive science; phenomenology; embodied cognition; dynamical systems theory; enactive approach; social cognition; interaction theory; evolutionary robotics. (shrink)

We argue that progress in our scientific understanding of the ‘social mind’ is hampered by a number of unfounded assumptions. We single out the widely shared assumption that social behavior depends solely on the capacities of an individual agent. In contrast, both developmental and phenomenological studies suggest that the personal-level capacity for detached ‘social cognition’ is a secondary achievement that is dependent on more immediate processes of embodied social interaction. We draw on the enactive approach to cognitive science to further (...) clarify this strong notion of ‘social interaction’ in theoretical terms. In addition, we indicate how this interaction theory could eventually be formalized with the help of a dynamical systems perspective on the interaction process, especially by making use of evolutionary robotics modeling. We conclude that bringing together the methods and insights of developmental, phenomenological, enactive and dynamical approaches to social interaction can provide a promising framework for future research. Keywords: theory of mind; cognitive science; phenomenology; embodied cognition; dynamical systems theory; enactive approach; social cognition; interaction theory; evolutionary robotics. (shrink)

Classically, the question of recognizing another subject is posed unilaterally, in terms of the observed behaviour of the other entity. Here, we propose an alternative, based on the emergent patterns of activity resulting from the interaction of both partners. We employ a minimalist device which forces the subjects to externalize their perceptual activity as trajectories which can be observed and recorded; the results show that subjects do identify the situation of perceptual crossing with their partner. The interpretation of the results (...) is guided by comparable evolutionary robotics simulations. There are two components to subjects’ recognition capacities: distinguishing mobile and fixed entities; and behaving so as to interact with their partner rather than with a mobile lure. The “Other” is characterized by the feature that there is sufficient regularity in the interactions to encourage the formation of anticipations; but sufficient indetermination that the actual behaviour is consistently surprising. Keywords: Recognition of other; perceptual crossing; evolutionary robotics. (shrink)

Classically, the question of recognizing another subject is posed unilaterally, in terms of the observed behaviour of the other entity. Here, we propose an alternative, based on the emergent patterns of activity resulting from the interaction of both partners. We employ a minimalist device which forces the subjects to externalize their perceptual activity as trajectories which can be observed and recorded; the results show that subjects do identify the situation of perceptual crossing with their partner. The interpretation of the results (...) is guided by comparable evolutionary robotics simulations. There are two components to subjects’ recognition capacities: distinguishing mobile and fixed entities; and behaving so as to interact with their partner rather than with a mobile lure. The “Other” is characterized by the feature that there is sufficient regularity in the interactions to encourage the formation of anticipations; but sufficient indetermination that the actual behaviour is consistently surprising. Keywords: Recognition of other; perceptual crossing; evolutionary robotics. (shrink)

We argue that progress in our scientific understanding of the ‘social mind’ is hampered by a number of unfounded assumptions. We single out the widely shared assumption that social behavior depends solely on the capacities of an individual agent. In contrast, both developmental and phenomenological studies suggest that the personal-level capacity for detached ‘social cognition’ is a secondary achievement that is dependent on more immediate processes of embodied social interaction. We draw on the enactive approach to cognitive science to further (...) clarify this strong notion of ‘social interaction’ in theoretical terms. In addition, we indicate how this interaction theory could eventually be formalized with the help of a dynamical systems perspective on the interaction process, especially by making use of evolutionary robotics modeling. We conclude that bringing together the methods and insights of developmental, phenomenological, enactive and dynamical approaches to social interaction can provide a promising framework for future research. Keywords: theory of mind; cognitive science; phenomenology; embodied cognition; dynamical systems theory; enactive approach; social cognition; interaction theory; evolutionary robotics. (shrink)

Communication is a fundamentally interactive phenomenon. Evolutionary biology recognises this fact in its definition of communication, in which signals are those actions that cause reactions, and where both action and reaction are designed for that reason. Where only one or the other is designed then the behaviours are classed as either cues or coercion. Since mutually dependent behaviours are unlikely to emerge simultaneously, the symmetry inherent in these definitions gives rise to a prediction that communication will only emerge if (...) cues or coercive behaviours do so first. They will then be co-opted for communication. A range of case studies, from animal signalling, evolutionary robotics, comparative psychology, and evolutionary linguistics are used to test this prediction. The first three are found to be supportive. However in the Embodied Communication Game, a recent experimental approach to the emergence of communication between adult humans, communication emerges even when cues or coerced behaviours are not possible. This suggests that humans are exceptional in this regard. It is argued that the reason for this is the degree to which we are able and compelled to read and interpret the behaviour of others in intentional terms. (shrink)

Embodied cognitive science has argued that cognition is embodied principally in virtue of grossmorphological and sensorimotor features. This thesis argues that cognition is also internally embodied in affective and fine-grained physiological features whose transformative roles remain mostly unnoticed in contemporary cognitive science. I call this ‘proper embodiment’. I approach this larger subject by examining various emotion theories in philosophy and psychology. These tend to emphasise one of the many gross components of emotional processes, such as ‘feeling’ or ‘judgement’ to the (...) detriment of the others, often leading to an artificial emotion-cognition distinction even within emotion science itself. Attempts to reconcile this by putting the gross components back together, such as JessePrinz’s “embodied appraisal theory”, are, I argue, destined to failure because the vernacular concept of emotion which is used as the explanandum is not a natural kind and is not amenable to scientific explication.I examine Antonio Damasio’s proposal that emotion is involved in paradigmatic ‘cognitive’ processing such as rational decision making and argue (1) that the research he discusses does not warrant the particular hypothesis he favours, and (2) that Damasio’s account, though in many ways a step in the right direction, nonetheless continues to endorse a framework which sees affect and cognition as separate (though now highly interacting) faculties. I further argue that the conflation of ‘affect’ and 'emotion' may be the source of some confusion in emotion theory and that affect needs to be properly distinguished from ‘emotion’. I examine some dissociations in the pain literature which give us further empirical evidence that, as with the emotions, affect is a distinct component along with more cognitive elements of pain. I then argue that affect is distinctive in being grounded in homeostatic regulative activity in the body proper. With the distinction between affect, emotion, and cognition in hand, and the associated grounding of affect in bodily activity, I then survey evidence that bodily affect is also involved in perception and in paradigmatic cognitive processes such as attention and executive function. I argue that this relation is not ‘merely’ casual. Instead, affect (grounded in fine-grained details of internal bodily activity) is partially constitutive of cognition, participating in cognitive processing and contributing to perceptual and cognitive phenomenology. Finally I review some work in evolutionary robotics which reaches a similar conclusion, suggesting that the particular fine details of embodiment, such as molecular signalling between both neural and somatic cells matters to cognition. I conclude that cognition is properly embodied’ in that it is partially constituted by the many fine-grained bodily processes involved in affect (as demonstrated in the thesis) and plausibly by a wide variety of other fine-grained bodily processes that likewise tend to escape the net of contemporary cognitive science. (shrink)

Communication is a fundamentally interactive phenomenon. Evolutionary biology recognises this fact in its definition of communication, in which signals are those actions that cause reactions, and where both action and reaction are designed for that reason. Where only one or the other is designed then the behaviours are classed as either cues or coercion. Since mutually dependent behaviours are unlikely to emerge simultaneously, the symmetry inherent in these definitions gives rise to a prediction that communication will only emerge if (...) cues or coercive behaviours do so first. They will then be co-opted for communication. A range of case studies, from animal signalling, evolutionary robotics, comparative psychology, and evolutionary linguistics are used to test this prediction. The first three are found to be supportive. However in the Embodied Communication Game, a recent experimental approach to the emergence of communication between adult humans, communication emerges even when cues or coerced behaviours are not possible. This suggests that humans are exceptional in this regard. It is argued that the reason for this is the degree to which we are able and compelled to read and interpret the behaviour of others in intentional terms. (shrink)

Robotization is an increasingly pervasive feature of our lives. Robots with high degrees of autonomy may cause harm, yet in sufciently complex systems neither the robots nor the human developers may be candidates for moral blame. John Danaher has recently argued that this may lead to a retribution gap, where the human desire for retribution faces a lack of appropriate subjects for retributive blame. The potential social and moral implications of a retribution gap are considerable. I argue that the retributive (...) intuitions that feed into retribution gaps are best understood as deontological intuitions. I apply a debunking argument for deontological intuitions in order to show that retributive intuitions cannot be used to justify retributive punishment in cases of robot harm without clear candidates for blame. The fundamental moral question thus becomes what we ought to do with these retributive intuitions, given that they do not justify retribution. I draw a parallel from recent work on implicit biases to make a case for taking moral responsibility for retributive intuitions. In the same way that we can exert some form of control over our unwanted implicit biases, we can and should do so for unjustifed retributive intuitions in cases of robot harm. (shrink)

Problem: How can radical constructivism gain wider recognition and acceptance? Method: Based on informal direct observation of other social and intellectual movements, the social and psychological dynamics and organizational imperatives of radical constructivism as an intellectual movement are discussed. Results: Various means of structuring the movement in order to gain wider acceptance are proposed. Implications: We hope that the paper has value in helping the radical constructivism movement evaluate where it has been and where it might go in terms of (...) wider social recognition and acceptance. (shrink)

Questions surrounding the evolution of cooperation, especially human cooperation, have driven research in many disciplines. Two key methodologies used to research and explain the evolution of cooperation are modeling and narrative construction. A number of scientists and philosophers have suggested that advancing research on the evolution of cooperation will require integrating models and narratives. But, relatively little has been said about what challenges exist to integrating models and narratives, how to go about integrating models and narratives, and what particular benefits (...) might be gained by accomplishing such integration. In this dissertation project, I address these questions in order to show how models and narratives can be integrated to produce better research on and explanations of the evolution of cooperation. The major challenge to integrating models and narratives concerning the evolution of cooperation that I address in this dissertation stems from the criticisms that such models and narratives lack empirical support. I answer this challenge by defending models and narratives from these criticisms. In the case of models, I argue both that at least some models of the evolution of cooperation have stronger empirical support than supposed by critics and that evolutionary robotics modeling approaches can be used to create even better models. In the case of narratives, I argue that several means of defending narratives from evidential challenges already developed by philosophers can be used to defend narratives about the evolution of cooperation as well. To show how narratives and models can be integrated to better research and explain the evolution of cooperation, I first establish an account of integration by drawing on the work of other philosophers. I then argue that models and narratives can provide certain benefits to each other via integration. Models can benefit from integration with narratives by using the narratives as sources of information as well as hypotheses to test. Indeed, as models are used to test such hypotheses, they also gain explanatory power. Narratives can benefit from integration with models by using the models as sources of support and constraint. Moreover, models can help deepen the understanding of historical contingency provided by narratives. (shrink)

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial, natural sciences, and philosophy. The question is, what at this stage of the development the inspiration from nature, specifically its computational models such as (...) info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach humanlevel intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature. (shrink)

Although the knowledge about biological systems has advanced exponentially in recent decades, it is surprising to realize that the very definition of Life keeps presenting theoretical challenges. Even if several lines of reasoning seek to identify the essence of life phenomenon, most of these thoughts contain fundamental problem in their basic conceptual structure. Most concepts fail to identify either necessary or sufficient features to define life. Here, we analyzed the main conceptual frameworks regarding theoretical aspects that have been supporting the (...) most accepted concepts of life, such as (i) the physical, (ii) the cellular and (iii) the molecular approaches. Based on an ontological analysis, we propose that Life should not be positioned under the ontological category of Matter. Yet, life should be better understood under the top-level ontology of “Process”. Exercising an epistemological approach, we propose that the essential characteristic that pervades each and every living being is the presence of organic codes. Therefore, we explore theories in biosemiotics and code biology in order to propose a clear concept of life as a macrocode composed by multiple inter-related coding layers. This way, as life is a sort of metaphysical process of encoding, the living beings became the molecular materialization of that process. From the proposed concept, we show that the evolutionary process is a fundamental characteristic for life’s maintenance but it is not necessary to define life, as many organisms are clearly alive but they do not participate in the evolutionary process (such as infertile hybrids). The current proposition opens a fertile field of debate in astrobiology, epistemology, biosemiotics, code biology and robotics. (shrink)

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial (deep learning, robotics), natural sciences (neuroscience, cognitive science, biology), and philosophy (philosophy of computing, philosophy of mind, natural philosophy). The question is, what (...) at this stage of the development the inspiration from nature, specifically its computational models such as info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach human-level intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature. (shrink)

Evolutionary ideas and modern biological knowledge have important roles to play in the understanding of human behaviour. Nevertheless, it is deeply misleading to regard humans as robots in the grip of their genes. A well designed brain should respond to the consequences of behaviour; if an understanding of the likely consequences can be achieved without actually performing the act, then a person who knows that they will be rewarded or punished for certain acts is bound to be influenced by (...) that knowledge. A brain designed in that way facilitates the evolution of societies with explicit social approval of certain activities and explicit disapproval of others. The evolutionary approach to psychology does not imply that individuals do not make free choices. Individuals clearly do make a big difference to what happens in their lives through their decisions. They may be surprised by the consequences of their own actions. A well designed brain should be able to anticipate the consequences of various courses of action and choose between them on the basis of their likely costs and benefits. Planning before doing is clearly of great advantage. People do make well considered decisions and they benefit from doing so. (shrink)

Learning from contemporary natural, formal, and social sciences, especially from current biology, as well as from humanities, particularly contemporary philosophy of nature, requires updates of our old definitions of cognition and intelligence. The result of current insights into basal cognition of single cells and evolution of multicellular cognitive systems within the framework of extended evolutionary synthesis (EES) helps us better to understand mechanisms of cognition and intelligence as they appear in nature. New understanding of information and processes of physical (...) (morphological) computation contribute to novel possibilities that can be used to inspire the development of abiotic cognitive systems (cognitive robotics), cognitive computing and artificial intelligence. (shrink)

Source: "This book addresses the fundamentals of machine ethics. It discusses abilities required for ethical machine reasoning and the programming features that enable them. It connects ethics, psychological ethical processes, and machine implemented procedures. From a technical point of view, the book uses logic programming and evolutionary game theory to model and link the individual and collective moral realms. It also reports on the results of experiments performed using several model implementations. Opening specific and promising inroads into the terra (...) incognita of machine ethics, the authors define here new tools and describe a variety of program-tested moral applications and implemented systems. In addition, they provide alternative readings paths, allowing readers to best focus on their specific interests and to explore the concepts at different levels of detail. Mainly written for researchers in cognitive science, artificial intelligence, robotics, philosophy of technology and engineering of ethics, the book will also be of general interest to other academics, undergraduates in search of research topics, science journalists as well as science and society forums, legislators and military organizations concerned with machine ethics.". (shrink)

Fear and concerns regarding AI and robots have existed for a long time, and the emergence of strong artificial intelligence, on par with human intelligence, is likely just a few decades away. The primary purpose of this article is to establish a theoretical framework for navigating the relationship between humans and this advanced form of artificial intelligence. This article first points out that the most fundamental characteristic of life is its continuous process of evolution and iteration. By analyzing the developmental (...) history of intelligence in different species, it can be observed that intelligence also exhibits a similar evolutionary phenomenon. Therefore, from this perspective, intelligence can be defined as a new form of information life. Under this premise, similarities and differences between information life forms and conventional biological life become apparent. The most significant distinction lies in the fact that the survival of biological life is based on non-replicable matter and energy, leading to extensive competition and food chain phenomena within ecosystems. In contrast, the survival of information life relies more on replicable information, fostering tendencies towards peace and communication. Based on this theoretical premise, there is a potential for a harmonious coexistence between humans and AI. This theory also provides guidance for the positive development of human society. (shrink)

Evolutionary thinking has expanded in the last decades, spreading from its traditional stronghold - the explanation of speciation and adaptation in Biology - to new domains including the human sciences. The essays in this collection attest to the illuminating power of evolutionary thinking when applied to the understanding of the human mind. The contributors to Cognition, Evolution and Rationality use an evolutionary standpoint to approach the nature of the human mind, including both cognitive and behavioral functions. Cognitive (...) science is by its nature an interdisciplinary subject and the essays use a variety of disciplines including the Philosophy of Science, the Philosophy of Mind, Game Theory, Robotics and Computational Neuroanatomy to investigate the workings of the mind. The topics covered by the essays range from general methodological issues to long-standing philosophical problems such as how rational human beings actually are. This book will be of interest across a number of fields, including philosophy, evolutionary theory and cognitive science. (shrink)