Introduction
In this course we introduce biosemiotics as a field of research that develops models of life processes focusing on their informational aspects. Peirce’s general concept of semiosis can be used to analyze such processes, and provide a powerful basis for understanding the emergence of meaning in living systems, by contributing to the construction of a theory of biological information. Peirce’s theory of sign action is introduced, and the relation between ‘information processing’ and sign processes is discussed, in fact, a semiotic definition of information is introduced. Three biosemiotic models of informational processes, at the behavioral and molecular levels, are developed, first, a model of genetic information processing in protein synthesis; second, a model of signal transduction in B-cell activation in the immune system; and, finally, a model of symbolic non-human primate communication. We also address some perspectives for the development of applied semiotic research in fields such as Artificial life, cognitive ethology, cognitive robotics, theoretical biology, and education.
Lectures
- Theoretical semiotics (
)In this lecture, we introduce theoretical notions one must consider to face the main problems on modeling biological information processes. - Multi-level model of emergent semiosis (I) ()In this lecture, we will summarize a systematic analysis of the variety of emergence theories and concepts developed by Stephan (1998,1999). This will lead us to pose fundamental questions that have to be answered (Lecture 3) in order to ascribe a precise meaning to the term “emergence” in the context of an analysis of biological semiosis.
- Multi-level model of emergent semiosis (II) ()In this lecture, we propose that the emergence of semiosis of different kinds can be understood as resulting from fundamental interactions in a triadically-organized hierarchical process. To grasp these interactions, we develop a model grounded on Stanley Salthe’s hierarchical structuralism.
- Semiotic systems ()In this lecture we introduce James Fetzer’s notion of semiotic system and explore biological examples of his conception.
- Biological applications ()In this lecture, we introduce the Peircean notion of information and then applied this model to studies about the genetic information system.
- Semiotic processes in the immune system ()In this lecture, we discuss functional and semiotic models of signaling pathways, focusing particularly on signal transduction in B-cell activation as a case study.
- Non-human primate communication ()In this lecture we approach ‘the meaning of alarm calls in vervet monkeys’ according to our model of biosemiotic processes.
- Perspectives for Applied Semiotics in Artificial Life Research ()In this lecture, a biologically inspired semiotic model is proposed in synthetic biology. In the first part of this lecture we investigate theoretical constraints about the feasibility of simulated semiosis. These constraints, which are basic requirements for the simulation of semiosis, refer to the synthesis of irreducible triadic relations (Sign – Object – Interpretant). We examine the organization of the triad S-O-I, that is, the relative position of its elements and how they relate to each other by determinative relations, and we suggest a meta-algorithm. At the second part we begin with a description of a general approach for conducting experiments with artificial creatures within a synthetic ethological context. Next, we describe how this approach was used to build a computational experiment regarding the emergence of self-organized symbols. Our experiment simulated a community of artificial creatures undergoing complex intra and inter-specific interactions in which meaning evolved over time, from a tabula rasa repertoire of random alarm-calls to a specific set of optimal referential alarm-calls. To design different kinds of creatures as well as innanimate elements of the environment, we applied theoretical constraints from the Peircean philosophy of sign and empirical constraints from neuroethology. Behaviors such as navigation, search, predation, evasion and cooperation were modeled as communication processes evolving within and across artificial brains of different kinds of creatures. Our results suggest that the constraints chosen were both necessary and sufficient to produce symbolic communication.