Upshot: We acknowledge that our model can be implemented with different reinforcement learning algorithms. Subsystem formation has been successfully demonstrated on the basal level, and in order to show full subsystem formation in the communication system at least both intentional utterances and acceptance/rejection need to be implemented. The comments about intrinsic vs extrinsic rewards made clear that this distinction is not helpful in the context of the constructivist paradigm but rather needs to be replaced by a critical reflection on whether (...) one has truly created autopoietic agents or just an engineering system. (shrink)

Future state maximisation offers a clear departure from both fixed reactive systems and systems that learn models based on reactive experience. In this commentary, I argue that FSX is not ….

Purpose: This article investigates the emergence of subsystems in societies as a solution to the double contingency problem. Context: There are two underlying paradigms: one is radical constructivism in the sense that perturbations are at the centre of the self-organising processes; the other is Luhmann’s double contingency problem, where agents learn anticipations from each other. Approach: Central to our investigation is a computer simulation where we place agents into an arena. These agents can learn to (a) collect food and/or (b) (...) steal food from other agents. In order to analyse subsystem formation, we investigate whether agents use both behaviours or just one of these, which is equivalent to determining the number of self-referential loops. This is detected with a novel measure that we call “prediction utilisation.” Results: During the simulation, symmetry breaking is observed. The system of agents divides itself up into two subsystems: one where agents just collect food and another one where agents just steal food from other agents. The ratio between these two populations is determined by the amount of food available. Key words: Social systems, constructivist paradigm, cybernetics, double contingency, symmetry breaking, emergence. (shrink)

Open peer commentary on the article ““Black Box” Theatre: Second-Order Cybernetics and Naturalism in Rehearsal and Performance” by Tom Scholte. Upshot: My aim is to show that “truthful” acting that emerges through improvisation is equivalent to the development of mutual forward models in the actors. If these models match those of the audience members, this is perceived as “truthful.”.

Motivation: Classical definitions of information, such as the Shannon information, are designed for open loop systems because they define information on a channel which has an input and an output. The main motivation of this paper is to present a closed loop information measure which is compatible with constructivist thinking. Design: Our information measure for a closed loop system reflects how additional sensor inputs are utilised to establish additional sensor-motor loops during learning. Our information measure is based on the assumption (...) that it is not optimal to stay reactive and that it is beneficial to become proactive through increased learning about the environment. Consequently our information measure gauges the utilisation of new sensor inputs to generate anticipatory actions. We call this information measure "predictive information" (PI). Findings: Our PI is zero if the organism uses only its reflex reactions. It grows when the organism is able to use other sensor inputs to preempt reflex reactions and is able to replace reflexes by anticipatory reactions. This has been demonstrated with a real robot that had to learn to avoid obstacles. Conclusion: PI is a new measure which is able to quantify anticipatory learning and, in contrast to the Shannon information, is calculated only at the inputs of an agent. This information measure has been successfully applied to a simple robot task but its application is neither limited to a certain task nor to a certain learning rule. (shrink)

Open peer commentary on the article “Constructivism and Computation: Can Computer-Based Modeling Add to the Case for Constructivism?” by Manfred Füllsack. Upshot: The environment is not slowly constructed by the agent but is an integral part of being an agent because both, agent and environment, are part of a closed loop system. By identifying the perturbations impacting on the loops, with the help of second-order cybernetics, the agent can identify them as its environment.

Esposito claims that current algorithms are divinatory. I agree with her, but for different reasons. Her point is that they are divinatory because they only use correlations, but current algorithms….