Heterarchy in biological systems: A logic-based dynamical model of abstract biological network derived from time-state-scale re-entrant form

Asynchronous time-space model for evolutionary market

An economic system is thought to be evolutionary growing. Economists investigate human decision-making by monetary value. However, the emergent property of the economy has not been explained. A model considering the extent of the monetary value is required. In this paper, a time-space model is proposed to elucidate the economic evolution of a market. Since the market activities are always open and realtime, the model of time and space is complicated. For the complexity, the probabilistic boundary and expectations under a low-possibility are introduced. Then, time and space cannot be separated and are defined as an asynchronous relationship. We apply this time-space model to the adaptive agent models of single and double auctions. The results of the numerical simulation indicate the intermittency in a broad area of the control parameter. This result concludes that the extent of monetary value can be a basis of the evolutionary market.

Modeling of decision-making process for moving straight using inverse Bayesian inference

Humans sometimes make unreasonable decisions when viewed in objective terms. Even in the real world, we may lose sense of direction by turning around the corner several times or mistaking the estimation of travel distance. We experimented in virtual space how we lose sense of direction under what circumstances. In the experiment, subjects viewed a three-dimensional space displayed on a computer display in the first person's perspective and were instructed to go straight from the start to the goal position. Results showed that unreasonable selections that strayed from the centerline connecting the start and goal positions were frequently made. The change in the direction is more influential than the change in the distance, and the angle of turning also affects. Furthermore, the subject's decision - making process was modeled using Bayesian inference and inverse Bayesian inference. Comparing the two models, when the decision-making pattern suddenly changed, the model by inverse Bayesian inference could follow up faster than the Bayesian inference.

Awareness as observational heterarchy

Libet et al. (1983) revealed that brain activity precedes conscious intention. For convenience in this study, we divide brain activity into two parts: a conscious field (CF) and an unconscious field (UF). Most studies have assumed a comparator mechanism or an illusion of CF and discuss the difference of prediction and postdiction. We propose that problems to be discussed here are a twisted sense of agency between CF and UF, and another definitions of prediction and postdiction in a mediation process for the twist. This study specifically examines the definitions throughout an observational heterarchy model based on internal measurement. The nature of agency must be emergence that involves observational heterarchy. Consequently, awareness involves processes having duality in the sense that it is always open to the world (postdiction) and that it also maintains self robustly (prediction).