Life has semiotic nature; and as life forms differ in their complexity, functionality, and adaptability, we assume that forms of semiosis also vary accordingly. Here we propose a criterion to distinguish between the primitive kind of semiosis, which we call “protosemiosis” from the advanced kind of semiosis, or “eusemiosis”. In protosemiosis, agents associate signs directly with actions without considering objects, whereas in eusemiosis, agents associate signs with objects and only then possibly with actions. Protosemiosis started from the origin of life, (...) and eusemiosis started when evolving agents acquired the ability to track and classify objects. Eusemiosis is qualitatively different from protosemiosis because it can not be reduced to a small number of specific signaling pathways. Proto-signs can be classified into proto-icons that signal via single specific interaction, proto-indexes that combine several functions, and proto-symbols that are processed by a universal subagent equipped with a set of heritable adapters. Prefix “proto” is used here to characterize signs at the protosemiotic level. Although objects are not recognized by protosemiotic agents, they can be reliably reconstructed by human observers. In summary, protosemiosis is a primitive kind of semiosis that supports “know-how” without “know-what”. Without studying protosemiosis, the biosemiotics theory would be incomplete. (shrink)
Biological evolution is often viewed narrowly as a change of morphology or allele frequency in a sequence of generations. Here I pursue an alternative informational concept of evolution, as preservation, advance, and emergence of functional information in natural agents. Functional information is a network of signs that are used by agents to preserve and regulate their functions. Functional information is preserved in evolution via complex interplay of copying and construction processes: the digital components are copied, whereas interpreting subagents together with (...) scaffolds, tools, and resources, are constructed. Some of these processes are simple and invariant, whereas others are complex and contextual. Advance of functional information includes improvement and modification of already existing functions. Although the genome information may change passively and randomly, the interpretation is active and guided by the logic of agent behavior and embryonic development. Emergence of new functions is based on the reinterpretation of already existing information, when old tools, resources, and control algorithms are adopted for novel functions. Evolution of functional information progressed from protosemiosis, where signs correspond directly to actions, to eusemiosis, where agents associate signs with objects. Language is the most advanced form of eusemiosis, where the knowledge of objects and models is communicated between agents. (shrink)
In contrast to the traditional relational semiotics, biosemiotics decisively deviates towards dynamical aspects of signs at the evolutionary and developmental time scales. The analysis of sign dynamics requires constructivism to explain how new components such as subagents, sensors, effectors, and interpretation networks are produced by developing and evolving organisms. Semiotic networks that include signs, tools, and subagents are multilevel, and this feature supports the plasticity, robustness, and evolvability of organisms. The origin of life is described here as the emergence of (...) simple self-constructing semiotic networks that progressively increased the diversity of their components and relations. Primitive organisms have no capacity to classify and track objects; thus, we need to admit the existence of proto-signs that directly regulate activities of agents without being associated with objects. However, object recognition and handling became possible in eukaryotic species with the development of extensive rewritable epigenetic memory as well as sensorial and effector capacities. Semiotic networks are based on sequential and recursive construction, where each step produces components that are needed for the following steps of construction. Construction is not limited to repair and reproduction of what already exists or is unambiguously encoded, it also includes production of new components and behaviors via learning and evolution. A special case is the emergence of new levels of organization known as metasystem transition. Multilevel semiotic networks reshape the phenotype of organisms by combining a mosaic of features developed via learning and evolution of cooperating and/or conflicting subagents. (shrink)
Principles of constructivism are used here to explore how organisms develop tools, subagents, scaffolds, signs, and adaptations. Here I discuss reasons why organisms have composite nature and include diverse subagents that interact in partially cooperating and partially conflicting ways. Such modularity is necessary for efficient and robust functionality, including mutual construction and adaptability at various time scales. Subagents interact via material and semiotic relations, some of which force or prescribe actions of partners. Other interactions, which I call “guiding”, do not (...) have immediate effects and do not disrupt the evolution and learning capacity of partner agents. However, they modify the extent of learning and evolutionary possibilities of partners via establishment of scaffolds and constraints. As a result, subagents construct reciprocal scaffolding for each other to rebalance their communal evolution and learning. As an example, I discuss guiding interactions between the body and mind of animals, where the pain system adjusts mind-based learning to the physical and physiological constraints of the body. Reciprocal effects of mind and behaviors on the development and evolution of the body includes the effects of Lamarck and Baldwin. (shrink)
Functional information means an encoded network of functions in living organisms from molecular signaling pathways to an organism’s behavior. It is represented by two components: code and an interpretation system, which together form a self-sustaining semantic closure. Semantic closure allows some freedom between components because small variations of the code are still interpretable. The interpretation system consists of inference rules that control the correspondence between the code and the function (phenotype) and determines the shape of the fitness landscape. The utility (...) factor operates at multiple time scales: short-term selection drives evolution towards higher survival and reproduction rate within a given fitness landscape, and long-term selection favors those fitness landscapes that support adaptability and lead to evolutionary expansion of certain lineages. Inference rules make short-term selection possible by shaping the fitness landscape and defining possible directions of evolution, but they are under control of the long-term selection of lineages. Communication normally occurs within a set of agents with compatible interpretation systems, which I call communication system. Functional information cannot be directly transferred between communication systems with incompatible inference rules. Each biological species is a genetic communication system that carries unique functional information together with inference rules that determine evolutionary directions and constraints. This view of the relation between utility and inference can resolve the conflict between realism/positivism and pragmatism. Realism overemphasizes the role of inference in evolution of human knowledge because it assumes that logic is embedded in reality. Pragmatism substitutes usefulness for truth and therefore ignores the advantage of inference. The proposed concept of evolutionary pragmatism rejects the idea that logic is embedded in reality; instead, inference rules are constructed within each communication system to represent reality, and they evolve towards higher adaptability on a long time scale. (shrink)
The target article by Denis Noble is an excellent overview of the illusions of the Modern Synthesis that still remains in textbooks despite of the recent criticism. Overcoming these illusions shows the active role of organisms in the evolutionary process and accounts for additional mechanisms such as plasticity of embryo development, epigenetic heredity, multilevel selection, Baldwin effect, and niche construction, which are components of the Extended Evolutionary Synthesis. Adding these mechanisms is certainly an important step forward, but I argue that (...) it is not sufficient for building a new theory of evolution. What is missing is a clear understanding of such notions as agency, autonomy, semiosis, interpretation, and goal-directedness, which so far belong to the humanities and have not been applied seriously in science. Organisms are autonomous and goal-directed semiotic agents capable of interpreting hereditary signs and making meaningful models of their environment. Evolutionary biology needs a semiotic vocabulary to talk about higher level functions in organisms, where specific molecules and mechanisms are only means for integrating functions over the life cycle and adapting to the environment without compromising organism integrity and identity. Such a vocabulary is being developed in biosemiotics; thus, I expect the emergence of a biosemiotic theory of evolution. (shrink)
The major merit of Rose's book is the elaboration of the idea of multilevel causation in different explanatory languages. Yet Rose's critique of “ultra-Darwinism” is not convincing. Rose argues that activity and self-replication are properties of organisms rather than genes, which contradicts his idea of multilevel causation. Also, Rose fails to develop the concept of multilevel selection.
Pragmatics, i.e., a system of values (or goals) in agent behavior, marks the boundary between physics and semiotics. Agents are defined as systems that are able to control their behavior in order to increase their values. The freedom of actions in agents is based on the distinction between macrocharacters that describe the state or stage, and micro-characters that are interpreted as memory. Signs are arbitrarily established relations between micro- and macro-characters that are anticipated to be useful for agents. Three kinds (...) of elementary signs (action, perception, and association) have been developed in agents via evolution and learning to support useful and flexible behaviors. The behavior of agents can be explained, predicted, and modified using the optimality principle, according to which agents select those actions that are expected to increase their value. However, agents may select actions based on their own model of the world, which have to be reconstructed in order to predict their behavior. Pragmatics in agents can be induced, learned from individual experience or natural selection, or adopted. (shrink)