Notion Of Free Energy Research Articles

Models of the Translation Process and the Free Energy Principle.

Translation process research (TPR) has generated a large number of models that aim at explaining human translation processes. In this paper, I suggest an extension of the monitor model to incorporate aspects of relevance theory (RT) and to adopt the free energy principle (FEP) as a generative model to elucidate translational behaviour. The FEP-and its corollary, active inference-provide a general, mathematical framework to explain how organisms resist entropic erosion so as to remain within their phenotypic bounds. It posits that organisms reduce the gap between their expectations and observations by minimising a quantity called free energy. I map these concepts on the translation process and exemplify them with behavioural data. The analysis is based on the notion of translation units (TUs) which exhibit observable traces of the translator's epistemic and pragmatic engagement with their translation environment, (i.e., the text) that can be measured in terms of translation effort and effects. Sequences of TUs cluster into translation states (steady state, orientation, and hesitation). Drawing on active inference, sequences of translation states combine into translation policies that reduce expected free energy. I show how the notion of free energy is compatible with the concept of relevance, as developed in RT, and how essential concepts of the monitor model and RT can be formalised as deep temporal generative models that can be interpreted under a representationalist view, but also support a non-representationalist account.

The two kinds of free energy and the Bayesian revolution.

The concept of free energy has its origins in 19th century thermodynamics, but has recently found its way into the behavioral and neural sciences, where it has been promoted for its wide applicability and has even been suggested as a fundamental principle of understanding intelligent behavior and brain function. We argue that there are essentially two different notions of free energy in current models of intelligent agency, that can both be considered as applications of Bayesian inference to the problem of action selection: one that appears when trading off accuracy and uncertainty based on a general maximum entropy principle, and one that formulates action selection in terms of minimizing an error measure that quantifies deviations of beliefs and policies from given reference models. The first approach provides a normative rule for action selection in the face of model uncertainty or when information processing capabilities are limited. The second approach directly aims to formulate the action selection problem as an inference problem in the context of Bayesian brain theories, also known as Active Inference in the literature. We elucidate the main ideas and discuss critical technical and conceptual issues revolving around these two notions of free energy that both claim to apply at all levels of decision-making, from the high-level deliberation of reasoning down to the low-level information processing of perception.

Associativité, symbolisation et entropie : propositions théoriques et cliniques

ObjectiveFree association is a founding concept of psychoanalytical therapies that refers to the way the patient will more or less freely pass from one representation to another. It helps to explore psychic reality and is also a therapeutic method useful in different clinical settings. Our goal, in this work, has been to study associativity with a double stance from psychoanalysis and cognitive neurosciences. Such an approach could help to improve the link between clinical and cognitive models. It also fosters our understanding of psychological processes during psychotherapy. Materials and methodsWe first propose a global overview of the historical origins of the concept of associativity in psychoanalysis. We analyze, in particular, how Freud started to develop the principles of free association with Emmy Von N. and how he progressively improved the definition and the use of this concept. We also study how associativity is closely related to the distinction between primary and secondary processes. We then expose and cross the psychoanalytical approach with research about associativity coming from cognitive neurosciences and neuropsychoanalysis. The impact of these research is finally analyzed from the point of view of clinical practice. ResultsAssociativity appears as a fruitful concept situated at the intersection between psychoanalysis and neurosciences. A first bridge is proposed between the research of Daniel Kahneman (System 1/System 2) and the distinction developed by Freud between primary and secondary processes. The notion of free energy is then analyzed as a common concept to psychoanalysis and cognitive models, especially in the work of Karl Friston concerning the way the brain tends to reduce free energy. Recent research about affective consciousness and default mode network research is also considered as being useful in order to study associativity through the concept of free energy and entropy. Associativity appears, from this point of view, as a way for the psyche to integrate high and low degree of entropy at different levels of organization of the brain. ConclusionsSymbolization is linked to several and specific forms of associativity processes. We propose to call “primary associativity” a first form of associativity that deals with primary processes. By contrast, secondary associativity rather concerns the impact of these processes at higher level of the psychic apparatus. The transition of one form of associativity to the other has a strong impact on the psychotherapeutic efficacy. We propose more precisely to call this transition process “transmodal symbolization”.