The concept of semantic information refers to the type of information that has some "significance" or "meaning" for a given system. Its use to describe how precisely the desired meaning is conveyed makes possible to characterize systems in terms of autonomous agents that are able to achieve an intrinsic goal or to accomplish a specific task. Two different types of semantic information are well recognized and used in the literature: i. 'stored' semantic information, which refers to information exchanged between a system and its environment in its initial distribution, and ii. 'observed' semantic information, which denotes the information that is dynamically acquired by a system to maintain its own existence. Both the concepts of stored and observed semantic information were first introduced by Kolchinsky and Wolpert in 2018.In this paper we present an approach to measure observed semantic information. Its quantitative measure is obtained for a smart drug delivery scenario where synthetic cells sense an environment made up of cancerous cells. These release a signal molecule that triggers the production of a cytotoxic drug by the synthetic cell. For the same scenario, the stored semantic information has already been computed. The main novel contribution compared to the evaluation of stored semantic information consists in a measure of the minimal perception of the environment [in bits] that allows a system to maintain its own functionality (as a proxy of its own existence) during its joint dynamic evolution with the environment, i.e. not decreasing its viability compared to full environment perception. Moreover, we provide a preliminary discussion about how the quantification of semantic information can contribute to better define what is meaningful to an agent. With this result we emphasize once again the role that "synthetic cells" have as new (bio)technological platform for theoretical and applied investigations of semantic information in biological systems.
Semantic Information as a Measure of Synthetic Cells’ Knowledge of the Environment
Lorenzo Del Moro;Maurizio Magarini;
2024-01-01
Abstract
The concept of semantic information refers to the type of information that has some "significance" or "meaning" for a given system. Its use to describe how precisely the desired meaning is conveyed makes possible to characterize systems in terms of autonomous agents that are able to achieve an intrinsic goal or to accomplish a specific task. Two different types of semantic information are well recognized and used in the literature: i. 'stored' semantic information, which refers to information exchanged between a system and its environment in its initial distribution, and ii. 'observed' semantic information, which denotes the information that is dynamically acquired by a system to maintain its own existence. Both the concepts of stored and observed semantic information were first introduced by Kolchinsky and Wolpert in 2018.In this paper we present an approach to measure observed semantic information. Its quantitative measure is obtained for a smart drug delivery scenario where synthetic cells sense an environment made up of cancerous cells. These release a signal molecule that triggers the production of a cytotoxic drug by the synthetic cell. For the same scenario, the stored semantic information has already been computed. The main novel contribution compared to the evaluation of stored semantic information consists in a measure of the minimal perception of the environment [in bits] that allows a system to maintain its own functionality (as a proxy of its own existence) during its joint dynamic evolution with the environment, i.e. not decreasing its viability compared to full environment perception. Moreover, we provide a preliminary discussion about how the quantification of semantic information can contribute to better define what is meaningful to an agent. With this result we emphasize once again the role that "synthetic cells" have as new (bio)technological platform for theoretical and applied investigations of semantic information in biological systems.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
