Workshop Topics and Call for Paper

Despite its remarkable achievements, AI continues to yearn for further extensions in basic and applied research. In the sub-divisions of AI still dedicated to the synthetic modeling of natural cognition, front-line research targets patterns that are increasingly autonomous, adaptive and integrative, and intends to ground them in the structural features and the form(s) of organization characterizing biological systems – from unicellular systems to complex organisms and their (social) aggregates. Currently, this research horizon includes a multitude of bio-inspired lines of inquiry, sharing a ‘bottom-up’ approach – or, in other theoretical words, an ‘emergence by design’ approach – to the construction of artificial or synthetic systems that function and behave like biological systems. 

The workshop Synthetic Approaches to Biology and Artificial Intelligence intends to select a series of original contributions related to this bio-inspired modeling of life and cognition, in its hard/soft/wet-ware or hybrid expressions. The primary aim is to promote the emergence of novel paradigms for AI, firmly grounded in SB and AL research, and capable of producing qualitative leaps into next generation of technological artifacts expressing adaptive, communicational, and integrative – “cognitive” – biological-like functions and behaviors.

• How the synthetic approach to biology, in its software, wetware and hardware forms, provide AI with new, relevant insights for the advancement in the scientific understanding of natural cognition? In which conditions, in what ways, in which domains could these synthetic explorations positively contribute to AI-based technologies? That is: What can the synthetic approach to biology, in its different expression, offer to AI?

• What’s the complexity threshold, the links, the rules, the topology, the forms, the boundaries of Artificial Life systems (chemical networks, synthetic cells and droplets, neural networks, swarm robotics, evolutionary agents, …) in order to display minimal adaptive, communicational, integrative – “cognitive” – functions/behaviors?

• How to design Artificial Life systems in robotic, computer science, synthetic biology domains that allow AI emergence, and how the latter compares with the biological counterparts?

This workshop aims at bringing together contributions related to these and related questions, and investigating one or more aspects of the (possible/actual) relationships between the synthetic approach to biology and AI.

The workshop will start with individual contributions, followed by a structured discussion, in the form of a round-table. The discussion aims at constituting a productive dialogue among the different specialists, a highly cross-disciplinary forum, engaging participants in generating answers to the many open questions in the field, and cooperate in the critical improvements of the projects and the ideas there presented. 

• Which are the groundings, the procedures, the expected results and the impacts of current research programs involving the synthetic approach to biology in AI?

• Can we, at the present time, plan concrete collaborations between computer science, robotics and synthetic biology in the scientific study of natural forms of cognition and intelligence? How?

• Can these cross-fertilizations contribute to the development of new forms of cognition and intelligence, alternative to the natural ones and to the existing forms of artificial cognition and intelligence?

We expect keynote and selected talks focused on conceptual and experimental issues related to the synthetic modeling of life and cognition, in any respect and in any domain. This way, we intend to put into focus the most advanced research relevant for the topic of Synthetic Approaches to Biology and Artificial Intelligence.

Final Program (Japan Standard Time, JST)

Wednesday 26 July 2023

17:10-17:20 L. Damiano. Welcome and Introduction to SB-AI 8

17:20-17:40 J. C. Letelier, Jorge Soto-Andrade, and Amaranta Valdéz-Zorrilla. Diagrams to understand Structural Coupling

17:40-17:55 S. Holler. Protocells, DNA and Information.

17:55-18:15 T. Veloz and S. Leijnen. The cognitive domain of a reaction network and its relation to the evolution of intelligence

18:15-18:30 General Discussion and Conclusion

Abstracts

• Diagrams to understand Structural Coupling

  • Juan Carlos Letelier, Jorge Soto-Andrade, and Amaranta Valdéz-Zorrilla, University of Chile

  • We explain, with examples, the important but cryptic notion of STRUCTURAL COUPLING.  Also, in the logic of using Category Theory to understand Quantum Mechanics, we introduce diagrams that help Us to reveal hidden connections behind Structural Coupling.

• Protocells, DNA and Information

  • Silvia Holler, CIBIO, University of Trento

  • Information is hidden in all the entities that surround us in everyday life. It can be found in cells and in their genetic code, but also in varying properties and/or behaviours of other types of systems. An exploratory study was performed where information are linked with protocells systems (ACDC H2020 project). Protocells are specifically coupled with DNA and organized depending on its quantity and base pairing. Population aggregation allows the collection of chemical polymers. Competing base pairing also guarantees the population disaggregation and the release of compounds hidden in the aggregates. Unconventional type of information will also be presented. They will be directly related to the variation of physio chemical properties of protocells. Many of the emergent phenomena of life may have arisen within classes of physio-chemical systems that can be composed of a diverse range of material going from: vesicles, oil droplets, cellular automata and reaction-diffusion systems. Given the stark differences in composition between these systems, it is clear that life like behaviors are not unique to human life but occur in many scenarios: information can be found and stored in all of them.

• The cognitive domain of a reaction network and its relation to the evolution of intelligence

  • Tomas Veloz (Vrije Universiteit Brussel) and Stefan Leijnen (Hogeschool Utrecht)

  • In the theory of autopoiesis, the notion of cognitive domain refers to the actions that an autopoietic system can execute without losing its identity. Despite the conceptual depth and relevance of this notion to the debates around origins of life and cognition, it has remained almost unexplored at the level of mathematical modeling. In this talk, we review the meaning of the cognitive domain concept, and provide a formalization of it using reaction networks. Namely, autopoietic systems are represented by chemical organizations, i.e. closed and self-maintaining reaction networks. Hence, the actions of an autopoietic system correspond to the reaction pathways that can be executed by a chemical organization. Therefore, the cognitive domain is defined as the collection of reaction pathways that can be implemented by an organization and that additionally ensure its self-maintenance.
    The latter seemingly trivial formalization of the notion of cognitive domain allows us to advance a less trivial framework, where the intelligence of an autopoietic system can be measured by the extent at which the cognitive domain of a reaction network is able to adapt so it is able to overcome challenges, corresponding to perturbations or processes that put under risk the autopoiesis of the system. In particular, we will advance formal notions of challenge, challenge counteracion, problem and solution in this context, explain how these notions relate to the resilience of a reaction network while illustrating the formalization with examples. We finally discuss how this framework can be applied to formalize related troubling notions such as autonomy and agency, and extend some new perspectives linking the notions of goal-directedness and the evolution of intelligence.