The journal Biosemiotics was envisioned by its founding editor, Marcello Barbieri, as a major periodical for interdisciplinary papers that integrate biology and semiotics. Since 2008 the journal has published 21 issues, including special issues on crucial problems such as the semiotics of perception, origins of mind, code biology, biohermeneutics, biosemiotic analysis of information and chance. The impact factor of the journal does not fully describe the significance of this journal, because the discipline of biosemiotics is young and remains in its (...) early phase of growth. As the new editorial team of Biosemiotics, we would like to express our gratitude to Dr. Barbieri for his excellent job as an editor, and ensure the readers that we are equally committed to maintain high standards and the scientific rigor of published papers. At the end of 2014 we reorganized the editorial board of the journal based on the credential and former activity of prospective members. The cu .. (shrink)

We propose here to clarify some of the relations existing between information and meaning by showing how meaningful information can be generated by a system submitted to a constraint. We build up definitions and properties for meaningful information, a meaning generator system and the domain of efficiency of a meaning (to cover cases of meaningful information transmission). Basic notions of information processing are used.

We humans experience ourselves as objects and as subjects. The distinction initiated by Kant between consciousness of oneself as object and consciousness of oneself as subject was a strict one. The rigidity of that distinction has been challenged by philosophers from the continental and the analytic traditions [1]. From another perspective, researches about animal self-awareness are widening the horizon of studies relative to the nature of self-consciousness [2]. These various perspectives introduce the interest about addressing consciousness of oneself as object (...) and as subject in an evolutionary background. We propose here to follow that path by using an existing scenario about the evolutionary nature of self-consciousness based on evolutions of representations and of inter-subjectivity [3, 4]. The scenario presents an evolutionary approach that can introduce self-consciousness as an acting body and self-consciousness as a thinking and feeling entity. These two aspects of self-consciousness are then compared to consciousness of oneself as object and as subject. The scenario proposes that an evolution of inter-subjectivity brought our pre-human ancestors to reach the capability of identifying with their conspecifics. This process coupled with an evolution of representations led our ancestors to build up representations of themselves as entities existing in the environment, like the conspecifics they identified with were represented. As conspecifics were perceived as existing and acting in the environment, identifying with them led to an elementary version of self-consciousness as an acting body, close to self-consciousness as object. Also, as different conspecifics could display very different behaviors like dominant or submitted, it was not possible to identify with them spontaneously. Knowing and understanding one's own identity as perceived by other members of the group was necessary for a pertinent identification with conspecifics. Such need to think about one's own characteristics and identity introduced self-consciousness as a thinking and feeling entity, close to an elementary version of self-consciousness as subject. In addition, the mental states of the thinking and feeling subject monitoring the actions of the body object address the common evolutionary source for consciousness of oneself as object and as subject. We present here that evolutionary approach to consciousness of oneself as object and as subject with the corresponding phylogenetic outcomes relative to the mind-body problem. Continuations are proposed. (shrink)

In this paper, we use the Meaning Generator System (MGS) presented at Gathering in Biosemiotics 2 [1] to analyse the evolution of meaningful information generation through different steps of the evolution of life. Taking as a starting point the usage of MGS for vital constraint satisfaction in basic life (paramecium), we develop its application for more complex living elements up to the case of non-human primate. The thread we follow is relative to the identification of new constraints that can appear (...) through evolution of life, and correspondingly participate to generation of new types of meaningful information. We show that beside the complexification of vital constraints to be satisfied, and in addition to the corresponding enrichment of their satisfaction processes, there is a step in evolution that naturally introduces some specific new constraint in living elements. This step is the one corresponding to the performance of self-representation. Self-representation appeared in evolution at the level of non-human primates. We present the content of self-representation and show that it has a direct consequence on the living element in terms of a new type of constraint to be satisfied. We show that this new constraint participates to the generation of a new set of meaningful information via the MGS, and that the satisfaction of the constraint introduces some natural formulation of emotion generation during the evolution of life. [1]. (shrink)

The management of meaningful information by biological entities is at the core of biosemiotics [Hoffmeyer 2010]. Intentionality, the ‘aboutness’ of mental states, is a key driver in philosophy of mind. Philosophers have been reluctant to use intentionality for non human animals. Some biologists have been in favor of it. J. Hoffmeyer has been using evolutionary intentionality and Peircean semiotics to discuss a biosemiotic approach to the problem of intentionality [Hoffmeyer 1996, 2012]. Also, recent philosophical studies are bringing new openings on (...) the subject of biological intentionality.[Asma 2014]. What we propose here is to use an existing system approach to meaning generation to introduce a link between biosemiotics and bio-intentionality at basic life level in an evolutionary perspective. Meanings do not exist by themselves. They have to be generated for a given reason by a defined entity. A system approach to meaning generation based on constraint satisfaction has been developped to that end: the Meaning Generator System (MGS) [Menant 2003a]. It has been used for biosemiotics in an evolutionary perspective [Menant 2003b, 2011]. To look at relating biosemiotics to intentionality through meaning genaration we recall the system structure of the MGS with the agent that contains it. Meaning generation and agent interfacing with environment make available components for the groundings of the generated meaning in terms of data, data processing, interfacing and constraint [Menant, 2011]. These groundings of the meaning can be in or out the agent containing the MGS. They display what the generated meaning is about. For basic life the ‘aboutness’ of the generated meaning relies on a ‘stay alive’ constraint that has to be satisfied (others constraints, like ‘live group life’, are to be introduced through the evolution of life). Such ‘aboutness’ of a generated meaning within basic life can be associated to an elementary biological intentionality, to a ‘bio-intentionality’. As biosemiotics deals with meaning management by biological entities, the relations introduced by the MGS between meaning generation and bio-intentionality introduce a link between biosemiotics and bio-intentionality for basic life. We present and develop that link. Besides making available a model usable for bio-intentionality, the proposed approach may also provide an entry point to the concept of intentionality without having to take into account human specificities like self-consciousness. It should also be noted that the approach takes life as a given and that the‘stay alive’ constraint brings in a teleological component. Such presentation of bio-intentionality calls for other developments and continuations. Some will be introduced. (shrink)

Understanding computation as “a process of the dynamic change of information” brings to look at the different types of computation and information. Computation of information does not exist alone by itself but is to be considered as part of a system that uses it for some given purpose. Information can be meaningless like a thunderstorm noise, it can be meaningful like an alert signal, or like the representation of a desired food. A thunderstorm noise participates to the generation of meaningful (...) information about coming rain. An alert signal has a meaning as allowing a safety constraint to be satisfied. The representation of a desired food participates to the satisfaction of some metabolic constraints for the organism. Computations on information and representations will be different in nature and in complexity as the systems that link them have different constraints to satisfy. Animals have survival constraints to satisfy. Humans have many specific constraints coming in addition. And computers will compute what the designer and programmer ask for. We propose to analyze the different relations between information, meaning and representation by taking an evolutionary approach on the systems that link them. Such a bottom-up approach allows starting with simple organisms and avoids an implicit focus on humans, which is the most complex and difficult case. To make available a common background usable for the many different cases, we use a systemic tool that defines the generation of meaningful information by and for a system submitted to a constraint [Menant, 2003]. This systemic tool allows to position information, meaning and representations for systems relatively to environmental entities in an evolutionary perspective. We begin by positioning the notions of information, meaning and representation and recall the characteristics of the Meaning Generator System (MGS) that link a system submitted to a constraint to its environment. We then use the MGS for animals and highlight the network nature of the interrelated meanings about an entity of the environment. This brings us to define the representation of an item for an agent as being the network of meanings relative to the item for the agent. Such meaningful representations embed the agents in their environments and are far from the Good Old Fashion Artificial Intelligence type ones. The MGS approach is then used for humans with a limitation resulting of the unknown nature of human consciousness. Application of the MGS to artificial systems brings to look for compatibilities with different levels of Artificial Intelligence (AI) like embodied-situated AI, the Guidance Theory of Representations, and enactive AI. Concerns relative to different types of autonomy and organic or artificial constraints are highlighted. We finish by summarizing the points addressed and by proposing some continuations. (shrink)