On the Emergence and Evolution of Mark-up Middlemen: An Inframarginal Model

This paper is aimed to provide an economic interpretation on the emergence and evolution of the specialised middlemen whose duty is to facilitate the transactions of goods and services in an economy. In a general equilibrium framework, the emergence and evolution of the specialised middlemen conforms to Adam Smith’s insight of deepening specialisation and the division of labour with the improvement in institutions and/or transaction technologies. Consequently, the emergence and the growth of the intermediation sector in both absolute and relative terms, the expansion of the network which provides transaction services, the evolution of market structure from autarky towards division of labour, the improvement in productivity, the reduction in wholesaling-retailing price dispersion, will be realised in concurrencymiddlemen, transaction efficiency, inframarginal economics

Gaussian Process Planning with Lipschitz Continuous Reward Functions: Towards Unifying Bayesian Optimization, Active Learning, and Beyond

This paper presents a novel nonmyopic adaptive Gaussian process planning (GPP) framework endowed with a general class of Lipschitz continuous reward functions that can unify some active learning/sensing and Bayesian optimization criteria and offer practitioners some flexibility to specify their desired choices for defining new tasks/problems. In particular, it utilizes a principled Bayesian sequential decision problem framework for jointly and naturally optimizing the exploration-exploitation trade-off. In general, the resulting induced GPP policy cannot be derived exactly due to an uncountable set of candidate observations. A key contribution of our work here thus lies in exploiting the Lipschitz continuity of the reward functions to solve for a nonmyopic adaptive epsilon-optimal GPP (epsilon-GPP) policy. To plan in real time, we further propose an asymptotically optimal, branch-and-bound anytime variant of epsilon-GPP with performance guarantee. We empirically demonstrate the effectiveness of our epsilon-GPP policy and its anytime variant in Bayesian optimization and an energy harvesting task.Comment: 30th AAAI Conference on Artificial Intelligence (AAAI 2016), Extended version with proofs, 17 page

Senior health care system

Senior Health Care System (SHCS) is created for users to enter participants\u27 conditions and store information in a central database. When users are ready for quarterly assessments the system generates a simple summary that can be reviewed, modified, and saved as part of the summary assessments, which are required by Federal and California law