The cilium/flagellum is a sensory-motile organelle ancestrally present in eukaryotic cells. For assembly cilia universally rely on intraflagellar transport (IFT), a specialised bidirectional transport process mediated by the ancestral and conserved IFT complex. Based on the homology of IFT complex proteins to components of coat protein I (COPI) and clathrin-coated vesicles, we propose that the non- vesicular, membrane-bound IFT evolved as a specialised form of coated vesicle transport from a protocoatomer complex. IFT thus shares common ancestry with all protocoatomer derivatives, (...) including all vesicle coats and the nuclear pore complex (NPC). This has major implications for the evolutionary origin of the cilium. First, it reinforces the tenet that duplication and divergence of pre-existing structures, rather than symbiosis, were the major themes during cilium evolution. Second, it suggests that the initial step in the autogenous origin of the cilium was the establishment of a membrane patch with transmembrane proteins transported by the ancestral vesicle-coating IFT complex. We propose a scenario for how the initial membrane patch gradually protruded to enhance exposure to the environment, then started to move, and finally compartmentalised to render receptor signalling and ciliary beating more efficient. BioEssays 28: 191–198, 2006. © 2006 Wiley periodicals, Inc. (shrink)

Large language models (LLMs) such as ChatGPT or Google’s Bard have shown significant performance on a variety of text-based tasks, such as summarization, translation, and even the generation of new...

Minimal cognition is an emerging field of research in the context of the life-mind continuity thesis. It stems from the idea that life and mind are strongly continuous, involving the same basic set of organisational principles. Minimal cognition has been sometimes regarded as the analysis of the minimum requirements for the emergence of cognitive phenomena. In the target article, Deacon describes the emergence of the autogenic system as an interpreting system that displays the simplest form of interpretive competence, its (...) most critical function being the capacity to re-present itself in ever new substrates and to interpret environmental conditions with respect to system self-maintenance. Since Deacon describes the autogen in cognitive terms, this article examines whether the autogen model can embody the critical disposition that underpins the emergence of minimal cognition. It finds that it does so, but argues that the autogenic system itself fails to be cognitive because it lacks the displacement of constraints that enable the semiotic scaffolding exhibited by life processes. The article then discusses the implications of the idea that autogenic processes underpin the emergence of minimal cognition for the life-mind continuity thesis. (shrink)

Deacon suggests the autogen as a minimal Kantian Whole where the parts exist for and by means of the whole. An Autogen is a “for whom” information is created. Semantics of information comes first, syntax later. There are no entailing laws for the emergence and evolution of new meanings, which likely happened long before template replication and the genetic code. The evolution of life and meaning are based on physics but rise creatively above physics.

Von der Prämisse ausgehend, dass die zentrale, wenn auch am grössten umstrittene, wenngleich am wenigsten aufgeklärte Frage des ganzen Evolutionsproblems sich auf die Art und Weise des ersten Entstehen der evoluirenden Merkmale bezieht, bringt der Verfasser eine allgemeine Klassifikation der Evolutionstheorien auf die autogenetische und statistische dar, indem jedoch die ersten mit schwer greifbaren Faktoren allzusehr überlastet zu sein scheinen, die zweiten aber mit der Notwendigkeit der Annahme einer unumgänglich dissipativen Irreversibilität der progressiven Entwicklung zu rechnen haben, die jedoch mit (...) keinen uns bekannten Evolutionsbeweisen bestätigt werden kann. Infolgedessen hebt der Verfasser ein dritter-eigener-Evolutionsgedanke hervor, und zwar in kombinatorischer Fassung, den er auf der Tatsache zu gründen sucht, dass erstens jeweilige Evolution vor allem eine Übertragung der sich mehr und mehr komplizierenden Zusammensetzungen der Eigenschaften von einer Geheration auf die andere darstellt, und zwar, zweitens, so, dass diese Übertragung einer vom Verfasser im Jahre 1938 aufgestellten allgemeinen Gleichung derMendel Gesetze gehorcht und Ausdruck einesNewtonschen Binomierens mit ununterbrochen wachsenden Koeffizienten der Kreuzungspotenz darstellt.Ferner, in einem Entwurf der historischen Entwicklung dieser Anschauung, sucht er,Johannsen's Stellung gegenüber, im Altertum an dieHeraclitische Mannigfaltigkeit-Einheits-Lehre anzuknüpfen, insbesondere aber sie mit demAnaxagorasschen Begriff von Homoiomerien in Zusammenhang zu bringen, die, in neueren Zeiten, lassen sich unmittelbar an den Mendelismus und denJohannsenschen Genbegriff anschliessen, um weiter, über diePearson's undPhilipchenko's allgemeine Gleichungen, zum Verfassers eigenen Begriff der genotypischen Binomionen zu gelangen. Das allmähliche kombinatorisch zustandekommende Kompliziertwerden derselben soll uns den Verlauf der sich abspielenden organismischen Evolution schematisch oder eigentlich symbolisch veranschaulichen.Endlich, sich über die rein theoretische Möglichkeit einer Annahme der noph weiteren, hinzukommenden und übergeordneten, Evolutionsfactoren überlegend, die auf diese oder jene Weise seine auf die natürliche Kombinatorik totalisierende, ordnende und zugleich auch inbezug auf die allgemeine Evolution richtende Einflüsse ausüben könnten, kommt der Verfasser zum Schluss, dass der wissenschaftliche Erkenntniswert solcher, dazu biologisch ziemlich geheimnisvoller Factoren, für die exacte Evolutionsuntersuchungen einstweilen recht gering bleiben müsste.En tenant compte du fait que le problème central, en même temps le plus controversé et obscur de l'évolution concerne la question de la première origine des caractères évolutifs, l'auteur émet, sous ce point de vue, une classification générale des théories de l'évolution, en les divisant en autogénétistes et statistiques, les premières étant surchargées par l'objection d'opérer avec des facteurs peu concrets et peu saisissables tandis que les secondes sont forcées d'admettre l'irréversibilité dissipative du développement progressif, qui cependant n'a pu être confirmée par aucune des évidences rapportées en faveur de l'évolution.En conséquence, l'auteur propose et soumet à une discussion un peu élargie une troisième possibilité-la sienne: celle de la conception de l'évolution notamment basée sur les processus combinatoires, en l'appuyant sur les faits incontestables, que chaque évolution consiste, avant tout, en une transmission ininterrompue de traits se compliquant de plus en plus à travers les générations successives, bien que les combinaisons impliquées soient gouvernées par l'équation générale des lois deMendel, établie par l'auteur en 1938, et faisant une expression des opérations du binôme newtonien, les indices de puissance duquel croissent graduellement.Dans une esquisse historique du développement préalable de cette conception, l'auteur retrace ses racines dans la philosophie grecque, en descendant jusqu'à la thèse deHeraclitedes alliages des multiplicités dans l'unité des choses et la retrouve avant tout dans la conception des homoïomeries d'Anaxagore, ce qui s'attache, dans les temps nouveaux, de la manière la plus immédiate, au mendélisme, à la conception du gène, émis parJohannsen, et aboutit, par l'intermédiaire des équations produites parPearson etPhilipchenko, à la notion des binomions introduits par lui-même pour déterminer les groupes seuls homogènes au cours de l'évolution progressive. Or, les complications combinatoires, graduelles mais croissantes, de ces combinaisons les plus naturelles constitueraient une suite schématique ou plutôt symbolique de l'évolution accomplissante.Enfin, en réfléchissant sur la possibilité théorique d'admission des facteurs totalitaires en surplus, ordonnant le jeu combinatoire bien qu'aussi directeurs par rapport aux tendences générales de l'évolution organique, l'auteur aboutit à la conclusion que la valeur explorative de tels facteurs, du reste bien mystérieux, pour les recherches précises du procédé de l'évolution serait cependant très restreinte. (shrink)

In this reply to our commentators, we respond to ethical concerns raised about the potential use (or misuse) of personalized LLMs for academic idea and prose generation, including questions about c...

The potential of using personalized Large Language Models (LLMs) or “generative AI” (GenAI) to enhance productivity in academic research, as highlighted by Porsdam Mann and colleagues (Porsdam Mann...

Artificial intelligence (AI), large language models (LLMs), such as Open AI’s ChatGPT, have a remarkable ability to process and generate human language but have also raised complex and novel ethica...

There is an apparent connection between reinforcement learning and agency. Artificial entities controlled by reinforcement learning algorithms are standardly referred to as agents, and the mainstream view in the psychology and neuroscience of agency is that humans and other animals are reinforcement learners. This article examines this connection, focusing on artificial reinforcement learning systems and assuming that there are various forms of agency. Artificial reinforcement learning systems satisfy plausible conditions for minimal agency, and those which use models of the environment (...) to perform forward search are capable of a form of agency which may reasonably be called action for reasons. (shrink)

In their recent paper “AUTOGEN: A Personalized Large Language Model for Academic Enhancement—Ethics and Proof of Principle,” Porsdam Mann et al. (2023) demonstrate a technique for fine-tuning the l...

Many philosophers are building a solid case in favour of the knowledge account of assertion (KAA). According to KAA, if one asserts that P one represents oneself as knowing that P. KAA has recently received support from linguistic data about prompting challenges, parenthetical positioning and predictions. In this article, I add another argument to this rapidly growing list: an argument from what I will call ‘reinforcing parenthesis’.

In this opinionated review, I draw attention to some of the contributions reinforcement learning can make to questions in the philosophy of mind. In particular, I highlight reinforcement learning's foundational emphasis on the role of reward in agent learning, and canvass two ways in which the framework may advance our understanding of perception and motivation.

Animals routinely adapt to changes in the environment in order to survive. Though reinforcement learning may play a role in such adaptation, it is not clear that it is the only mechanism involved, as it is not well suited to producing rapid, relatively immediate changes in strategies in response to environmental changes. This research proposes that counterfactual reasoning might be an additional mechanism that facilitates change detection. An experiment is conducted in which a task state changes over time and the (...) participants had to detect the changes in order to perform well and gain monetary rewards. A cognitive model is constructed that incorporates reinforcement learning with counterfactual reasoning to help quickly adjust the utility of task strategies in response to changes. The results show that the model can accurately explain human data and that counterfactual reasoning is key to reproducing the various effects observed in this change detection paradigm. (shrink)

I argue for the role of reinforcement learning in the philosophy of mind. To start, I make several assumptions about the nature of reinforcement learning and its instantiation in minds like ours. I then review some of the contributions of reinforcement learning methods have made across the so-called 'decision sciences.' Finally, I show how principles from reinforcement learning can shape philosophical debates regarding the nature of perception and characterisations of desire.

We investigate how Reinforcement Learning methods can be used to solve the production selection and production ordering problem in ACT‐R. We focus on four algorithms from the Q learning family, tabular Q and three versions of Deep Q Networks, as well as the ACT‐R utility learning algorithm, which provides a baseline for the Q algorithms. We compare the performance of these five algorithms in a range of lexical decision tasks framed as sequential decision problems.

In this paper I examine how the constituent elements of a firm's organizational structure affect the ethical behavior of workers. The formal features of organizations I examine are the compensation practices, performance and evaluation systems, and decision-making assignments. I argue that the formal organizational structure, which is distinguished from corporate culture, is necessary, though not sufficient, in solving ethical problems within firms. At best the formal structure should not undermine the ethical actions of workers. When combined with a strong culture, (...) however, the organizational structure may be sufficient in promoting ethical conduct. While helpful, ethics training and corporate codes are neither necessary nor sufficient in promoting ethical behavior within firms. (shrink)

Behaving ethically depends on the ability to recognize that ethical issues exist, to see from an ethical point of view. This ability to see and respond ethically may be related more to attributes of corporate culture than to attributes of individual employees. Efforts to increase ethical standards and decrease pressure to behave unethically should therefore concentrate on the organization and its culture. The purpose of this paper is to discuss how total quality (TQ) techniques can facilitate the development of a (...) cooperative corporate culture that promotes and encourages ethical behavior throughout an organization. (shrink)

A deep reinforcement learning-based computational guidance method is presented, which is used to identify and resolve the problem of collision avoidance for a variable number of fixed-wing UAVs in limited airspace. The cooperative guidance process is first analyzed for multiple aircraft by formulating flight scenarios using multiagent Markov game theory and solving it by machine learning algorithm. Furthermore, a self-learning framework is established by using the actor-critic model, which is proposed to train collision avoidance decision-making neural networks. To achieve higher (...) scalability, the neural network is customized to incorporate long short-term memory networks, and a coordination strategy is given. Additionally, a simulator suitable for multiagent high-density route scene is designed for validation, in which all UAVs run the proposed algorithm onboard. Simulated experiment results from several case studies show that the real-time guidance algorithm can reduce the collision probability of multiple UAVs in flight effectively even with a large number of aircraft. (shrink)

Rachlin rightly highlights behavioural reinforcement, conditional cooperation, and framing. However, genes may explain part of the variance in altruistic behaviour. Framing cannot be used to support his theory of altruism. Reinforcement of acts is not identical to reinforcement of patterns of acts. Further, many patterns of acts could be reinforced, and Rachlin's altruism is not the most likely candidate.

Relational database management system is the most popular database system. It is important to maintain data security from information leakage and data corruption. RDBMS can be attacked by an outsider or an insider. It is difficult to detect an insider attack because its patterns are constantly changing and evolving. In this paper, we propose an adaptive database intrusion detection system that can be resistant to potential insider misuse using evolutionary reinforcement learning, which combines reinforcement learning and evolutionary learning. The model (...) consists of two neural networks, an evaluation network and an action network. The action network detects the intrusion, and the evaluation network provides feedback to the detection of the action network. Evolutionary learning is effective for dynamic patterns and atypical patterns, and reinforcement learning enables online learning. Experimental results show that the performance for detecting abnormal queries improves as the proposed model learns the intrusion adaptively using Transaction Processing performance Council-E scenario-based virtual query data. The proposed method achieves the highest performance at 94.86%, and we demonstrate the usefulness of the proposed method by performing 5-fold cross-validation. (shrink)