Evolution of Doctoral Co-Supervision at the University of the Basque Country (Upv/Ehu)

Barandika, Gotzone; Astorkiza, Inmaculada; González-Abrisketa, Olatz; Portillo, Eva; Simón, Edurne

doi:10.21125/inted.2021.1838

Cited by 1 publication

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“…4 The processes that constitute and produce the organism as an agent , include its regular and relatively stable patterns of sensorimotor behavior. These patterns of sensorimotor behavior have been argued to also exhibit the key properties of autonomy—they depend upon operationally closed sensorimotor networks made up of co-enabling bodily and environmental processes (Di Paolo, 2005 ; Barandiaran, 2008 ; Egbert and Barandiaran, 2014 ; Di Paolo et al, 2017 ; Ramírez-Vizcaya and Froese, 2020 ). Think for example of habits like smoking cigarettes or drinking coffee when you wake up in the morning.…”

Section: Introductionmentioning

confidence: 99%

“…Recall our proposal is to use sensorimotor autonomy as a biologically-based design principle for building artificial agents (Barandiaran, 2008 ; Egbert and Barandiaran, 2014 ; Di Paolo et al, 2017 ; Ramírez-Vizcaya and Froese, 2020 ). The idea is that habits are self-sustaining patterns of activity that constitute a systemic identity for the agent relative to a sensorimotor domain.…”

Section: Introductionmentioning

confidence: 99%

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The Problem of Meaning: The Free Energy Principle and Artificial Agency

2022

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Biological agents can act in ways that express a sensitivity to context-dependent relevance. So far it has proven difficult to engineer this capacity for context-dependent sensitivity to relevance in artificial agents. We give this problem the label the “problem of meaning”. The problem of meaning could be circumvented if artificial intelligence researchers were to design agents based on the assumption of the continuity of life and mind. In this paper, we focus on the proposal made by enactive cognitive scientists to design artificial agents that possess sensorimotor autonomy—stable, self-sustaining patterns of sensorimotor interaction that can ground values, norms and goals necessary for encountering a meaningful environment. More specifically, we consider whether the Free Energy Principle (FEP) can provide formal tools for modeling sensorimotor autonomy. There is currently no consensus on how to understand the relationship between enactive cognitive science and the FEP. However, a number of recent papers have argued that the two frameworks are fundamentally incompatible. Some argue that biological systems exhibit historical path-dependent learning that is absent from systems that minimize free energy. Others have argued that a free energy minimizing system would fail to satisfy a key condition for sensorimotor agency referred to as “interactional asymmetry”. These critics question the claim we defend in this paper that the FEP can be used to formally model autonomy and adaptivity. We will argue it is too soon to conclude that the two frameworks are incompatible. There are undeniable conceptual differences between the two frameworks but in our view each has something important and necessary to offer. The FEP needs enactive cognitive science for the solution it provides to the problem of meaning. Enactive cognitive science needs the FEP to formally model the properties it argues to be constitutive of agency. Our conclusion will be that active inference models based on the FEP provides a way by which scientists can think about how to address the problems of engineering autonomy and adaptivity in artificial agents in formal terms. In the end engaging more closely with this formalism and its further developments will benefit those working within the enactive framework.

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