Towards a Theory of Awareness at ICAART 2024

At the ICAART 2024 Conference in Rome we had a Special Session organized by Luc Steels on the Awareness Inside topic funded by the EIC Pathfinder programme.

In the session I presented the initial developments towards a theory of awareness that the ASLab team is doing inside the CORESENSE and METATOOL projects.

We did a short, ten minute presentation, and after that we had an interesting conversation around the ideas presented and the possibility of developing a complete model-based theory of aware agents.

The presentation addressed the possibility of having a solid theory of awareness both for humans and machines and what are the elements that such a theory should have. We talked about two of these elements: the clear delimitation of a domain of phenomena, and the essential concepts that are the cornerstones of the theory.

These were the concepts that we proposed/discussed:

  • Sensing: The production of information for the subject from an object.
  • Perceiving: The integration of the sensory information bound to an object into a model of the object.
  • Model: Integrated actionable representation; an information structure that sustains a modelling relation.
  • Engine: Set of operations over a model.
  • Inference: Derive conclusions from the model. Apply engines to model.
  • Valid inference: A inference whose result matches the phenomenon at the modelled object.
  • Exert a model: Perform valid inferences from the model.
  • Understanding: Achieving exertability of a model of the object/environment.
  • Specific understanding: Understanding concerning a specific set of exertions.
  • Mission understanding: Understanding concerning a set of mission-bound exertions.
  • Omega understanding: Understanding all possible exertions of a model in relation to an object.
  • Awareness: Real-time understanding of sensory flows.
  • Self-awareness: Subject-bound awareness. Awareness concerning inner perception.

Get the complete presentation:

And the paper:

Siri Hustvedt – The Delusions of Certainty

Siri Hustvedt, The Delusions of Certainty, Simon & Schuster, 2016.

Thanks. After reading the book I am less deluded than when I started. I now know that Hustvedt is an educated, well-read erudite. I now know that Hustvedt doesn’t like men, information, and computers nor technology in general. I now know that singular cases are not supportive of any theoretical stance, unless it is your stance. I now know that data is always biased if takes you to a different opinion from literature mainstream.

This book is worth reading. It is engaging, informative and challenging. It contains tons of valuable references for anyone interested in studying the mind. It shows how delusional is our own perspective of ourselves. It clearly shows that humanities are not keeping apace with the evolution of the human world and keep themselves deeply bound to renaissance ideas on humans.

Read it.

A new Horizon Europe project: CoreSense

We have signed a grant agreement with the EC to coordinate a new research project on intelligent robotics. The CoreSense project will develop a new hybrid cognitive architecture to make robots capable of understanding and being aware of what is going on. The project will start on October 1, 2022 will span four years (2022-2026) and joins six partners across europe in an effort to push forward the limits of robotic cognition.

Cognitive robots are augmenting their autonomy, enabling them to deployments in increasingly open-ended environments. This offers enormous possibilities for improvements in human economy and wellbeing. However, it also poses strong risks that are difficult to assess and control by humans. The trend towards increased autonomy conveys augmented problems concerning reliability, resilience, and trust for autonomous robots in open worlds. The essence of the problem can be traced to robots suffering from a lack of understanding of what is going on and a lack of awareness of their role in these situations. This is a problem that artificial intelligence approaches based on machine learning are not addressing well. Autonomous robots do not fully understand their open environments, their complex missions, their intricate realizations, and the unexpected events that affect their performance. An improvement in the capability to understand of autonomous robots is needed.

The CoreSense project tries to provide a solution to this need in the form of a AI theory of understanding, a theory of robot awareness, some enginering-grade reusable software assets to apply these theories in real robots. The project will build three demonstrations of its capability to augment resilience of drone teams, augment flexibility of manufacturing robots, and augment human alignment of social robots.

In summary, CoreSense will develop a cognitive architecture for autonomous robots based on a formal concept of understanding, supporting value-oriented situation understanding and self-awareness to improve robot flexibility, resilience and explainability.

There are six project partners:

Universidad Politécnica de Madrid – ES – Coordinator
Delft University of Technology – NL
Fraunhofer IPA – DE
Universidad Rey Juan Carlos – ES
PAL Robotics – ES
Irish Manufacturing Research – IR

Principal Investigator: Ricardo Sanz

Premio Innovatech 2020 a la tecnología inTelos

El equipo UPM ASLab + TU Delft ha obtenido el Primer Premio en el concurso UPM_innovatech 2T Challenge de 2020.

Esta es una iniciativa de desafío competitivo para investigadores, pionera en España, que busca reconocer y premiar las tecnologías más innovadoras de la Universidad Politécnica de Madrid y contribuir a su desarrollo y comercialización.

La tecnología presentada por el equipo ASLab+TUDelft, InTelos, es el resultado de años de investigación en sistemas auto-conscientes en ASLab. Esta es una tecnología que permite emplear el conocimiento de ingeniería para dotar al sistema de capacidades cognitivas de auto-percepción y control que le dotan de una mayor adaptabilidad, resiliencia y autonomía. Es una tecnología resultante del proyecto ASys.