A Psychogenetic Algorithm for Behavioral Sequence Learning

This work presents an original algorithmic model of some essential features of psychogenetic theory, as was proposed by J.Piaget. Specifically, we modeled some elements of cognitive structure learning in children from 0 to 4 months of life. We are in fact convinced that the study of well-established cognitive models of human learning can suggest new, interesting approaches to problem so far not satisfactorily solved in the field of machine learning. Further, we discussed the possible parallels between our model and subsymbolic machine learning and neuroscience. The model was implemented and tested in some simple experimental settings, with reference to the task of learning sensorimotor sequences

Two Kinds of Adaptation, Two Kinds of Relativity

This paper presents a review of adaptation concepts at the evolutionary, environmental, neural, sensory, mental and mathematical levels, including Helson’s and Parducci’s theories of perception and category judgments. Two kinds of adaptation can be clearly distinguished. The first, known as level adaptation, refers to the shift of the neutral perception level to the average stimulus value. It results in a single reference point and stimuli changes represented in absolute terms. This concept is employed by Prospect Theory, which assumes that gains and losses are perceived as monetary amounts. The second kind of adaptation refers to the adjustment of perception sensitivity to stimuli range. It results in two reference points (minimum and maximum stimulus) and stimuli changes perceived in relative terms. Both range adaptation and range relativity are well documented phenomena and have even been confirmed by the creators of Prospect Theory. This makes room for another decision making theory based on the range relativity approach. As shown by Kontek (2009), such a theory would not require the concept of probability weighting to describe lottery experiments or behavioral paradoxes.Adaptation-Level Theory, Range-Frequency Theory, Prospect Theory

Two Kinds of Adaptation, Two Kinds of Relativity

This paper presents a review of adaptation concepts at the evolutionary, environmental, neural, sensory, mental and mathematical levels, including Helson’s and Parducci’s theories of perception and category judgments. Two kinds of adaptation can be clearly distinguished. The first, known as level adaptation, refers to the shift of the neutral perception level to the average stimulus value. It results in a single reference point and stimuli changes represented in absolute terms. This concept is employed by Prospect Theory, which assumes that gains and losses are perceived as monetary amounts. The second kind of adaptation refers to the adjustment of perception sensitivity to stimuli range. It results in two reference points (minimum and maximum stimulus) and stimuli changes perceived in relative terms. Both range adaptation and range relativity are well documented phenomena and have even been confirmed by the creators of Prospect Theory. This makes room for another decision making theory based on the range relativity approach. As shown by Kontek (2009), such a theory would not require the concept of probability weighting to describe lottery experiments or behavioral paradoxes

On Mental Transformations

The paper presents an alternative interpretation of the experimental data published by Kahneman and Tversky in their 1992 study "Advances in Prospect Theory”, which describes the Cumulative version of their Prospect Theory from 1979. It was assumed that, apart from the operations made during the initial stage of problem resolution, which Prospect Theory defines as Editing (here generalized as Mental Adaptation), other mental transformations such as Prospect Scaling (resulting from Focused Attention) and Logarithmic Perception of Financial Stimuli should be considered when analyzing the experimental data. This led to the design of an explicit, simple and symmetric solution without the use of the probability weighting function. The double S-type function obtained (the aspiration function) resembles the utility curve specified by the Markowitz hypothesis (1952) and substitutes the fourfold pattern of risk attitudes introduced by Cumulative Prospect Theory. The results presented constitute a basis for negating Prospect Theory as a theory which correctly describes how decisions are made under conditions of risk and may signal a return to a description of people’s behavior that only relies on the utility-like function

On Mental Transformations

This paper presents an alternative interpretation of the experimental data published by Kahneman and Tversky in their 1992 paper describing Cumulative Prospect Theory. It was assumed that mental transformations such as mental adaptation, prospect scaling, and logarithmic perception should be considered when analyzing the experimental data. This led to the design of a solution that did not require the probability weighting function. The double S-type function obtained (the decision utility) resembles the utility curve specified by the Markowitz hypothesis (1952) and substitutes the fourfold pattern of risk attitudes introduced by Cumulative Prospect Theory

On mental transformations

This paper presents an alternative interpretation of the experimental data published by Kahneman and Tversky in their 1992 paper describing Cumulative Prospect Theory. It was assumed that mental transformations such as mental adaptation, prospect scaling, and logarithmic perception should be considered when analyzing the experimental data. This led to the design of a solution that did not require the probability weighting function. The double S-type function obtained (the decision utility) resembles the utility curve specified by the Markowitz hypothesis (1952) and substitutes the fourfold pattern of risk attitudes introduced by Cumulative Prospect Theory

Affective Transformations

The Affective Turn has lost its former innocence and euphoria. Affect Studies and its adjacent disciplines have now to prove that they can cope with the return of the affective real that technology, economy, and politics entail. Two seemingly contradictory developments serve as starting points for this volume. First, technological innovations such as affective computing, mood tracking, sentiment analysis, and social robotics all share a focus on the recognition and modulation of human affectivity. Affect gets measured, calculated, controlled. Secondly, recent developments in politics, social media usage, and right-wing journalism have contributed to a conspicuous rise of hate speech, cybermobbing, public shaming, “felt truths,” and resentful populisms. In a very specific way, politics as well as power have become affective. Affect gets mobilized, fomented, unleashed. When the ways we deal with our affectivity get unsettled in such a dramatic fashion, we have to rethink our ethical, aesthetical, political as well as legal regimes of affect organization

Affective Transformations: Politics - Algorithms - Media

The Affective Turn has lost its former innocence and euphoria. Affect Studies and its adjacent disciplines have now to prove that they can cope with the return of the affective real that technology, economy, and politics entail. Two seemingly contradictory developments serve as starting points for this volume. First, technological innovations such as affective computing, mood tracking, sentiment analysis, and social robotics all share a focus on the recognition and modulation of human affectivity. Affect gets measured, calculated, controlled. Secondly, recent developments in politics, social media usage, and right-wing journalism have contributed to a conspicuous rise of hate speech, cybermobbing, public shaming, "felt truths," and resentful populisms. In a very specific way, politics as well as power have become affective. Affect gets mobilized, fomented, unleashed. When the ways we deal with our affectivity get unsettled in such a dramatic fashion, we have to rethink our ethical, aesthetical, political as well as legal regimes of affect organization