The Synthetic Approach to Biology and the Cognitive Sciences

(SA-BCS 2018)

Developing an Epistemology for the Synthetic Sciences of Life and Cognition

Satellite Workshop @ Alife 2018 -- Tokyo -- July 25, 2018 (15.30 - 19.00)

Organizing Committee:

Program

Welcoming note from the organizers - L. Damiano (University of Messina) and P. Stano (University of Salento)

15,30 – 16,00 Introduction - L. Damiano (University of Messina) - The synthetic method. Proposing a framework to the synthetic sciences of life and cognition

16,00 – 16,25 Keynote Talk 1- T. Froese (National Autonomous University of Mexico) - Is there room for intrinsic normativity in a synthetic system?

16,25 – 16,50 Keynote Talk 2 - J. Tani (Okinawa Institute of Science and Technology) - Emergentist Account for Non-Reductive Consciousness: From Neurorobotics Study

16,50 – 17,00 Discussion

17,30 – 17,50 Coffee Break

17,30 – 17,50 Selected Talk 1 - H. Kojima and T. Ikegami (University of Tokyo) - Artificial Cognitive Map Systems using Generative Deep Neural Networks

17,50 – 18,10 Selected Talk 2 - B. Valotta (University of Messina)- Towards a Cybernetics of Cybernetics

18,10 – 18,35 Keynote Talk 3 - P. Dumouchel (Ritsumeikan University) - Synthetic Methodology and Ontology

18,35 – 19,00 Discussion



Introduction

In line with the main topic of Alife 2018 – A new epistemology for Artificial Life and Complex Systems – the SA-BCS 2018 workshop intends to address the open epistemological issues related to the general methodological approach supporting the synthetic exploration of life and cognition. We refer to the so-called “Understanding by building” approach (Pfeifer and Scheier, 1999), originally and mainly called “the Synthetic Method” (Ross, 1935).

In its most generic expression, this method prescribes scientists to test scientific hypotheses on living and cognitive processes, lato sensu, through the construction and empirical exploration of synthetic models, that is: software models (i.e., simulations), hardware models (i.e., robotic platforms), wetware models (i.e., artificial biochemical systems), and/or mixed models.

The goal is generally twofold: improving current scientific hypotheses on the mechanisms underlying the target processes, in order to positively contribute to the scientific understanding of life and cognition; building better computational and/or engineering artifacts, able to exploit these mechanisms to enhance their performances. Since the age of Proto-Cybernetics (Cordeschi, 2002), when the Synthetic Method was introduced, considerable work has been done by specialists to define ways of synthetically modeling living and cognitive phenomena within the growing set of sciences of the artificial – AL and AI in primis, but also Synthetic and Computational Biology, Computer Science, Developmental, Cognitive, Epigenetic, Evolutionary and Social Robotics, among others.

The impressive advancements achieved so far in the synthetic exploration of life and cognition make it even more important to address the question of how pertinent this form of modeling is for the scientific knowledge of life and cognition, and how it is capable of capturing and penetrating the complexity of the processes under investigation.

What are the status and the value of the insights coming from the exploration of synthetic models of life and cognition? Are there criteria to warrant a positive transfer of knowledge from the sciences of the artificial to traditional sciences of life and cognition? Can systems built with different materials, and different organizations, be considered models of natural living and cognitive systems? If yes, in what sense, under what conditions, and in what ways? Can simple abstract models be useful to investigate complex phenomena? How and to what extent?

Questions of these kinds, if left unanswered, threaten the legitimacy of the Synthetic Method, as well as its effective integration among the explorative practices accepted by science as sources of valuable insights.

The main idea guiding the SA-BCS 2018 is that the most fruitful epistemological reflection is produced neither by epistemologists, nor by scientists themselves, but by the dialogue between these specialists, especially when it is referred to concrete projects and processes of scientific investigation.

On this basis, the SA-BCS 2018 workshop intends to gather specialists in epistemology and the synthetic modeling of life and cognition. Its main aim is to create a highly cross-disciplinary forum engaging its participants in generating a fruitful discussion directed to find answers to the epistemological doubts listed above, and to relevant theoretical, heuristic and methodological issues pertinent to address them.

The format of the workshop will include keynote and selected talks. To both invited and selected speakers, we will ask to focus the talks on one or more open questions related to the synthetic modeling of life and cognition, and to address them based on the presentation and critical discussion of concrete frontier synthetic research on life and cognition, and related concrete models.

This way, we intend to develop an epistemological reflection that, on one side, is in principle encompassing all the current forms of the synthetic investigation of life and cognition, and, on the other side, is grounded in actual front-line research, and able to tackle issues and address doubts that emerge in the effective practice of the synthetic modeling of life and cognition.


Call for Abstracts

In line with the main topic of Alife 2018 – "A new epistemology for Artificial Life and Complex Systems" – the SA-BCS 2018 workshop intends to address the open epistemological issues related to the general methodological approach supporting the synthetic exploration of life and cognition – the so-called "Understanding by building" approach (Pfeifer and Scheier, 1999).

  • What is the status and the value of the insights coming from the exploration of synthetic models of life and cognition?
  • Are there criteria to warrant a positive transfer of knowledge from the sciences of the artificial to traditional sciences of life and cognition?
  • Can systems built with different materials, and different embodiments, be considered effective models of natural living and cognitive systems?
  • Can simple abstract models be useful to investigate complex phenomena? How and to what extent?
  • Do hardware, software and wetware synthetic models have different explanatory powers?
  • Is the synthetic approach blurring classic dichotomies such as 'science/engineering', and 'artificial/natural'?
  • What are the roles of synthetic models in scientific explanation of natural phenomena? On what characteristics of these models are these roles grounded?

We are interested in submissions of original answers to these and other epistemological open questions related to the synthetic modeling of life and cognition, and which address them based on the presentation and critical discussion of concrete frontier synthetic research on life and cognition, and related concrete models.

We accept submissions in the form of an abstract related to frontier research in the context of the sciences of the artificial (AL, AI, Synthetic Biology, Computational Biology, Computer Science, Developmental, Cognitive, Epigenetic, Evolutionary and Social Robotics, Computer Science, among others), of the related traditional sciences (Biology and the Cognitive Sciences, lato sensu), and of Philosophy of Science and Epistemology.

Important Dates

  • Abstract Due: April 15, 2018
  • Notification of Acceptance: April 22, 2018
  • Workshop: July 25, 2018 (from 15.30 to 19.00)

How to submit an abstract

If you would like to contribute to the SA-BCS 2018 workshop, please send an email to Luisa Damiano (e-mail) or Pasquale Stano (e-mail) a single pdf file that includes:

  1. The title and the authors of your contribution
  2. The abstract of your talk (300-500 words, bibliography excluded)

About the SA-BCS 2018 workshop

"A new epistemology for Artificial Life and Complex Systems" is the main topic of Alife 2018. Coherently with this topic, the SA-BCS 2018 workshop intends to address the open epistemological issues related to the general methodological approach supporting the synthetic exploration of life and cognition. We refer to the so-called "Understanding by building" approach (Pfeifer and Scheier, 1999), originally and mainly called "the Synthetic Method" (Ross, 1935). In its most generic expression, it prescribes scientists to test scientific hypotheses on living and cognitive processes, lato sensu, through the construction and empirical exploration of synthetic models, that is: software models (i.e., simulations), hardware models (i.e., robotic platforms), wetware models (i.e., artificial biochemical systems), and/or mixed models. The goal is generally twofold: improving current scientific hypotheses on the mechanisms underlying the target processes, in order to positively contribute to the scientific understanding of life and cognition; building better computational and/or engineering artifacts, able to exploit these mechanisms to enhance their performances.

Since the age of Proto-Cybernetics, when the Synthetic Method was introduced, considerable work has been done by specialists to define ways of synthetically model living and cognitive phenomena within the growing set of sciences of the artificial – AL and AI in primis, but also Synthetic and Computational Biology, Computer Science, Developmental, Cognitive, Epigenetic, Evolutionary and Social Robotics, among others.

The impressive advancements achieved so far in the synthetic exploration of life and cognition make it even more important to address the question of how pertinent this form of modeling is for the scientific knowledge of life and cognition, and how it is capable of capturing and penetrating the complexity of the processes under investigation.

What is the status and the value of the insights coming from the exploration of synthetic models of life and cognition? Are there criteria to warrant a positive transfer of knowledge from the sciences of the artificial to traditional sciences of life and cognition? Can systems built with different materials, and different embodiments, be considered effective models of natural living and cognitive systems? Can simple abstract models be useful to investigate complex phenomena? How and to what extent?

Questions of this kind, if left unanswered, threaten the legitimacy of the Synthetic Method, as well as its effective integration among the explorative practices accepted by science as sources of valuable insights.

The main idea guiding the SA-BCS 2018 is that the most fruitful epistemological reflection is produced neither by epistemologists, nor by scientists on their own, but by the dialogue between these specialists, especially when referring to concrete projects and processes of scientific investigation. On this basis, the SA-BCS 2018 workshop intends to gather specialists in epistemology and the synthetic modeling of life and cognition. Its main aim is to create a highly cross-disciplinary forum engaging its participants in generating a fruitful discussion directed to find answers to the epistemological doubts listed above, and to relevant theoretical, heuristic and methodological issues pertinent to address them.

The format of the workshop will include keynotes and selected talks. To both invited and selected speakers, we will ask to focus the talks on one or more open questions related to the synthetic modeling of life and cognition, and to address them based on the presentation and critical discussion of concrete frontier synthetic research on life and cognition, and related concrete models. This way, we intend to develop an epistemological reflection that, on one side, is in principle encompassing all the current forms of the synthetic investigation of life and cognition, and the different models that the sciences of the artificial produce, and, on the other side, is always grounded in actual front-line research, and able to tackle issues and address doubts that emerge in the effective practice of the synthetic modeling of life and cognition.