Learning in evolutionary environments

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Endogenous Networks in Random Population Games

Population learning in dynamic economies has been traditionally studied in over-simplified settings where payoff landscapes are very smooth. Indeed, in these models, all agents play the same bilateral stage-game against any opponent and stage-game payoffs reflect very simple strategic situations (e.g. coordination). In this paper, we address a preliminary investigation of dynamic population games over `rugged' landscapes, where agents face a strong uncertainty about expected payoffs from bilateral interactions. We propose a simple model where individual payoffs from playing a binary action against everyone else are distributed as a i.i.d. U[0,1] r.v.. We call this setting a `random population game' and we study population adaptation over time when agents can update both actions and partners using deterministic, myopic, best reply rules. We assume that agents evaluate payoffs associated to networks where an agent is not linked with everyone else by using simple rules (i.e. statistics) computed on the distributions of payoffs associated to all possible action combinations performed by agents outside the interaction set. We investigate the long-run properties of the system by means of computer simulations. We show that: (i) allowing for endogenous networks implies higher average payoff as compared to "frozen" networks; (ii) the statistics employed to evaluate payoffs strongly affect the efficiency of the system, i.e. convergence to a unique (multiple) steady-state(s) or not; (iii) for some class of statistics (e.g. MIN or MAX), the likelihood of efficient population learning strongly depends on whether agents are change-averse or not in discriminating between options delivering the same expected payoff.Dynamic Population Games, Bounded Rationality, Endogenous Networks, Fitness Landscapes, Evolutionary Environments, Adaptive Expectations.

Learning in Evolutionary Environments

The purpose of this work is to present a sort of short selective guide to an enormous and diverse literature on learning processes in economics. We argue that learning is an ubiquitous characteristic of most economic and social systems but it acquires even greater importance in explicitly evolutionary environments where: a) heterogeneous agents systematically display various forms of "bounded rationality"; b) there is a persistent appearance of novelties, both as exogenous shocks and as the result of technological, behavioural and organisational innovations by the agents themselves; c) markets (and other interaction arrangements) perform as selection mechanisms; d) aggregate regularities are primarily emergent properties stemming from out-of-equilibrium interactions. We present, by means of examples, the most important classes of learning models, trying to show their links and differences, and setting them against a sort of ideal framework of "what one would like to understand about learning...". We put a signifiphasis on learning models in their bare-bone formal structure, but we also refer to the (generally richer) non-formal theorising about the same objects. This allows us to provide an easier mapping of a wide and largely unexplored research agenda.Learning, Evolutionary Environments, Economic Theory, Rationality

SACCHAROMYCES CEREVISIAE BIODIVERSITY IN MONFERRATO, NORTH WEST ITALY, AND SELECTION OF INDIGENOUS STARTER CULTURES FOR BARBERA WINE PRODUCTION

The aim of this study was to examine the biodiversity of Saccharomyces cerevisiae isolates from Barbera grapes and musts, from the Monferrato area, in the Piedmont region – North West Italy. An interdelta element PCR analysis was used to identify and discriminate 636 S. cerevisiae isolates at a strain level. Ninety-six S. cerevisiae that showed different molecular fingerprints were characterized through physiological tests and laboratory scale fermentations. A chemical analysis of experimental wines obtained from inoculated fermentations showed significant differences between the wines. The main variables considered in the strain differentiation were the residual sugars and the production of acetic acid, which ranged from 148.64 to 3.44 g/l and from 0.20 to 0.60 g/l, respectively. As a consequence, strain variability should be considered as a relevant resource to select suitable starter cultures in order to improve or characterize wines with a close bond to the geographic region

Advanced Oxidation Protein Products-Modified Albumin Induces Differentiation of RAW264.7 Macrophages into Dendritic-Like Cells Which Is Modulated by Cell Surface Thiols.

Local accumulation of Advanced Oxidation Protein Products (AOPP) induces pro-inflammatory and pro-fibrotic processes in kidneys and is an independent predictor of renal fibrosis and of rapid decline of eGFR in patients with chronic kidney disease (CKD). In addition to kidney damage, circulating AOPP may be regarded as mediators of systemic oxidative stress and, in this capacity, they might play a role in the progression of atherosclerotic damage of arterial walls. Atherosclerosis is a chronic inflammatory disease that involves activation of innate and adaptive immunity. Dendritic cells (DCs) are key cells in this process, due to their role in antigen presentation, inflammation resolution and T cell activation. AOPP consist in oxidative modifications of proteins (such as albumin and fibrinogen) that mainly occur through myeloperoxidase (MPO)-derived hypochlorite (HOCl). HOCl modified proteins have been found in atherosclerotic lesions. The oxidizing environment and the shifts in cellular redox equilibrium trigger inflammation, activate immune cells and induce immune responses. Thus, surface thiol groups contribute to the regulation of immune functions. The aims of this work are: (1) to evaluate whether AOPP-proteins induce activation and differentiation of mature macrophages into dendritic cells in vitro; and (2) to define the role of cell surface thiol groups and of free radicals in this process. AOPP-proteins were prepared by in vitro incubation of human serum albumin (HSA) with HOCl. Mouse macrophage-like RAW264.7 were treated with various concentrations of AOPP-HSA with or without the antioxidant N-acetyl cysteine (NAC). Following 48 h of HSA-AOPP treatment, RAW264.7 morphological changes were evaluated by microscopic observation, while markers of dendritic lineage and activation (CD40, CD86, and MHC class II) and allogeneic T cell proliferation were evaluated by flow cytometry. Cell surface thiols were measured by AlexaFluor-maleimide binding, and ROS production was assessed as DCF fluorescence by flow cytometry. HSA-AOPP induced the differentiation of RAW264.7 cells into a dendritic-like phenotype, as shown by morphological changes, by increased CD40, CD86 and MHC class II surface expression and by induction of T cell proliferation. The cell surface thiols dose dependently decreased following HSA-AOPP treatment, while ROS production increased. NAC pre-treatment enhanced the amount of cell surface thiols and prevented their reduction due to treatment with AOPP. Both ROS production and RAW264.7 differentiation into DC-like cells induced by HSA-AOPP were reduced by NAC. Our results highlight that oxidized plasma proteins modulate specific immune responses of macrophages through a process involving changes in the thiol redox equilibrium. We suggest that this mechanism may play a role in determining the rapid progression of the atherosclerotic process observed in CKD patients