An Embodied AI Approach to Measures of the Self

What are the prerequisites for the development of an artificial self? How does it change during development and bodily changes? Are the computational models suitable for explaining properties of the self in humans? These are the questions we have addressed in our project “Prerequisites for the development of an artificial self” within the first phase of the SPP. An important aspect that was raised during our collaborations within the SPP are the ways of measuring selfhood in humans and artificial agents. This addresses questions of adaptivity and predictability for a sense of agency or a sense of control, and the effects of bodily interactions of agents with their environment. Answering these questions will also help evaluating the selfhood of different implementations of artificial intelligent agents.

We address measures of the self in this project in the following steps: First, we start with a computational predictive model that allows for a basic sense of agency and body ownership and implement it in different experimental setups of robot interaction. We investigate measures of the self in two methodologically different ways: based on properties of the computational models and their instantiation in artificial agents, and based on behavioural observations inspired by variations of a sensorimotor Turing Test. Finally, we investigate whether the developed measures can account for testing disturbances of the self, in particular in cases where there is an imbalance between predicted and perceived information.

PI:  Prof. Dr. Verena Hafner

PhD Students: Yasmin Kim Georgie

Student Assistant: Ilja Porohovoj

Publications:

Hafner V, Hommel B, Kayhan E, Lee D, Paulus M and Verschoor S (2022). Editorial: The Mechanisms Underlying the Human Minimal Self. Front. Psychol. 13:961480. doi: 10.3389/fpsyg.2022.961480

Tim Julian Möller, Yasmin Kim Georgie, Guido Schillaci, Martin Voss, Verena Vanessa Hafner, Laura Kaltwasser (2021). Computational models of the “active self” and its disturbances in schizophrenia, Consciousness and Cognition, Volume 93, 2021, 103155, ISSN 1053-8100, https://doi.org/10.1016/j.concog.2021.103155.

Ciria, A., Schillaci, G., Pezzulo, G., Hafner, V.V. & Lara, B. (2021). Predictive Processing in Cognitive Robotics: a Review. Neural Computation (2021) 33 (5): 1402–1432.

Nguyen, P.D.H., Georgie, Y.K., Kayhan, E., Eppe, M., Hafner, V.V. and Wermter, S. (2021). Sensorimotor representation learning for an “active self” in robots: A model survey. KI – Künstliche Intelligenz. German Journal of Artificial Intelligence. Special Issue: Developmental Robotics. 01/2021. Springer. DOI 10.1007/s13218-021-00703-z

Eppe, M., Hafner, V.V., Nagai, Y., Wermter, S. (Eds.) (2021). Editorial. Special Issue on Developmental Robotics. KI – Künstliche Intelligenz. Vol. 35, Issue 1. German Journal of Artificial Intelligence. Springer.

Hafner, V.V., Loviken, P., Pico Villalpando, A., Schillaci, G. (2020). Prerequisites for an Artificial Self. Frontiers in Neurorobotics 14:5. doi:10.3389/fnbot.2020.00005. ISSN 1662-5218.

Georgie, Y.K., Schillaci, G. and Hafner, V.V. (2019). An interdisciplinary overview of developmental indices and behavioral measures of the minimal self, 2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob). Oslo, Norway, pp. 129-136. DOI 10.1109/DEVLRN.2019.8850703