In this paper, we make a review on the concepts of rationality across several different fields, namely in economics, psychology and evolutionary biology and behavioural ecology. We review how processes like natural selection can help us understand the evolution of cognition and how cognitive biases might be a consequence of this natural selection. In the end we argue that humans are not irrational, but rather rationally bounded and we complement the discussion on how quantum cognitive models can contribute for the modelling and prediction of human paradoxical decisions.
It is the focus of this work to extend and study the previously proposed quantum-like Bayesian networks to deal with decision-making scenarios by incorporating the notion of maximum expected utility in influence diagrams. The general idea is to take advantage of the quantum interference terms produced in the quantum-like Bayesian Network to influence the probabilities used to compute the expected utility of some action. This way, we are not proposing a new type of expected utility hypothesis. On the contrary, we are keeping it under its classical definition. We are only incorporating it as an extension of a probabilistic graphical model in a compact graphical representation called an influence diagram in which the utility function depends on the probabilistic influences of the quantum-like Bayesian network. Our findings suggest that the proposed quantum-like influence digram can indeed take advantage of the quantum interference effects of quantum-like Bayesian Networks to maximise the utility of a cooperative behaviour in detriment of a fully rational defect behaviour under the prisoner's dilemma game.
We elaborate a quantum model for the meaning associated with corpora of written documents, like the pages forming the World Wide Web. To that end, we are guided by how physicists constructed quantum theory for microscopic entities, which unlike classical objects cannot be fully represented in our spatial theater. We suggest that a similar construction needs to be carried out by linguists and computational scientists, to capture the full meaning carried by collections of documental entities. More precisely, we show how to associate a quantum-like 'entity of meaning' to a 'language entity formed by printed documents', considering the latter as the collection of traces that are left by the former, in specific results of search actions that we describe as measurements. In other words, we offer a perspective where a collection of documents, like the Web, is described as the space of manifestation of a more complex entity - the QWeb - which is the object of our modeling, drawing its inspiration from previous studies on operational-realistic approaches to quantum physics and quantum modeling of human cognition and decision-making. We emphasize that a consistent QWeb model needs to account for the observed correlations between words appearing in printed documents, e.g., co-occurrences, as the latter would depend on the 'meaning connections' existing between the concepts that are associated with these words. In that respect, we show that both 'context and interference (quantum) effects' are required to explain the probabilities calculated by counting the relative number of documents containing certain words and co-ocurrrences of words.
AN ICONIC physics experiment may be hiding more than we ever realised about the nature of reality. The classic "double-slit" experiment reveals the strange duality of the quantum world, but it may behave more strangely than we thought – and could challenge one of the most closely held assumptions of quantum mechanics. Revisiting it could help unify quantum mechanics with the other pillar of theoretical physics – Einstein's general relativity – a challenge that has so far proven intractable. The double-slit experiment involves shining a light at two close-together slits placed in front of a screen. Our classical view of the world suggests that photons of light should pass through one slit or the other, and thus create two parallel bands on the screen behind.
We present a quantum-like model in that contexts (complexes of physical, mental, or social conditions) are represented by complex probability amplitudes. This approach gives the possibility to apply the quantum formalism for probabilities induced in any domain of science. In this paper we propose a model of brain functioning based on the quantum-like (QL) representation of mental contexts. In this model brain can be considered as a QL (but not conventional quantum) computer. We discuss a possible mechanism of the QLrepresentation of information in the brain. It is based on processing of information at two different time scales: precognitive (fine) and cognitive (coarse).