Meta-learning: Bayesian or quantum?

Abundant experimental evidence illustrates violations of Bayesian models across various cognitive processes. Quantum cognition capitalizes on the limitations of Bayesian models, providing a compelling alternative. We suggest that a generalized quantum approach in meta-learning is simultaneously more robust and flexible, as it retains all the advantages of the Bayesian framework while avoiding its limitations.

A Quantum Predictive Brain: Complementarity Between Top-Down Predictions and Bottom-Up Evidence.

Predictive brain theory challenges the general assumption of a brain extracting knowledge from sensations and considers the brain as an organ of inference, actively constructing explanations about reality beyond its sensory evidence. Predictive brain has been formalized through Bayesian updating, where top-down predictions are compared with bottom-up evidence. In this article, we propose a different approach to predictive brain based on quantum probability-we call it Quantum Predictive Brain (QPB).

Estimating Successful Internal Mobility: A Comparison Between Structural Equation Models and Machine Learning Algorithms.

Internal mobility often depends on predicting future job satisfaction, for such employees subject to internal mobility programs. In this study, we compared the predictive power of different classes of models, i.e.

Affect and Cognition in Managerial Decision Making: A Systematic Literature Review of Neuroscience Evidence.

How do affect and cognition interact in managerial decision making? Over the last decades, scholars have investigated how managers make decisions. However, what remains largely unknown is the interplay of affective states and cognition during the decision-making process. We offer a systematization of the contributions produced on the role of affect and cognition in managerial decision making by considering the recent cross-fertilization of management studies with the neuroscience domain.

More Thumbs Than Rules: Is Rationality an Exaptation?

The literatures on bounded and ecological rationality are built on adaptationism-and its associated modular, cognitivist and computational paradigm-that does not address or explain the evolutionary origins of rationality. We argue that the adaptive mechanisms of evolution are not sufficient for explaining human rationality, and we posit that human rationality presents exaptive origins, where exaptations are traits evolved for other functions or no function at all, and later co-opted for new uses. We propose an embodied reconceptualization of rationality-embodied rationality-based on the reuse of the perception-action system, where many neural processes involved in the control of the sensory-motor system, salient in ancestral environments have been later co-opted to create-by tinkering-high-level reasoning processes, employed in civilized niches.

Vigor and aspiration levels in neuroeconomics.

In this contribution, we criticize the demanding assumption of vigor that economic agents are maximizers. We discuss the link between vigor and subjective value through the alternative notion of aspiration levels, arguing that vigor can help articulate the ecological balance - central in bounded and ecological rationality - between minimum expected reward (aspiration level) and the efforts made for its attainment.

Enhancing Organizational Memory Through Virtual Memoryscapes: Does It Work?

Enhancing cognitive memory through virtual reality represents an issue, that has never been investigated in organizational settings. Here, we compared a virtual memoryscape (treatment) - an immersive virtual environment used by subjects as a shared memory tool based on spatial navigation - with respect to the traditional individual-specific mnemonic tool based on the "method of loci" (control). A memory task characterized by high ecological validity was administered to 82 subjects employed by large banking group.

Economic Reasoning and Interaction in Socially Extended Market Institutions.

An important part of what it means for agents to be situated in the everyday world of human affairs includes their engagement with economic practices. In this paper, we employ the concept of cognitive institutions in order to provide an enactive and interactive interpretation of market and economic reasoning. We challenge traditional views that understand markets in terms of market structures or as processors of distributed information.

Satisficing as an alternative to optimality and suboptimality in perceptual decision making.

Rahnev & Denison's (R&D) critique of optimality in perceptual decision making leads either to implicitly retaining optimality as a normative benchmark or disregarding the normative approach altogether. We suggest that "bounded rationality," and particularly the "satisficing" criterion, would help dispense with optimality while salvaging normativity. We also suggest that satisficing would provide a parsimonious and robust explanation for perceptual behavior.