The lack of a well established theory of consciousness is a major difficulty in the construction of machines that express some of the functionalities associated to them. The ASys long term project intends the construction of assets for engineering any-scale, self-aware autonomous systems. A core element in this effort is the proposal of an architecture for consciousness of general applicability. In this article we analyze some of the current problems present in the construction of machines based on cognitive models and propose a model-based strategy to enhance the rigor of the theorization on consciousness and its mapping into realizations in technical systems.@en

There is an increasing demand for more autonomous systems. Enhancing systems with self-aware and self- adaptation capabilities can provide a solution to meet resilience needs. This article proposes a general design solution to build autonomous systems capable of run-time reconfiguration. The solution leverages Model-Driven Engineering with Model-Based Cognitive Control. The key idea is the integration of a metacontroller in the control architecture of the autonomous system, capable of perceiving the dysfunctional components of the control system and reconfiguring it, if necessary, at runtime. At the core of the metacontroller's operation lies a model of the system's functional architecture, which can be generated from the engineering modeling of the system.@en

Phenomenological states are generally considered sources of intrinsic motivation for autonomous biological agents. In this paper we will address the issue of exploiting these states for robust goal-directed systems. We will provide an analysis of consciousness in terms of a precise definition of how an agent ?understands? the informational flows entering the agent. This model of consciousness and understanding is based in the analysis and evaluation of phenomenological states along potential trajectories in the phase space of the agents. This implies that a possible strategy to follow in order to build autonomous but useful systems is to embed them with the particular, ad-hoc phenomenology that captures the requirements that define the system usefulness from a requirements-strict engineering viewpoint.@en