The dynamics of firms in a micro-to-macro model: The role of training, learning and innovation

We analyze the co-evolution of the performances of firms and of the economy in an evolutionary micro-to-macro model of the Swedish economy. The model emphasizes the interactions between human capital (or competences) and technological change at the firm level and their effects on aggregate growth, taking into account the micro-macro feedbacks. The model features learning-by-doing, incremental and radical innovations, user-producer learning at the firm level, and a change in the techno-economic paradigm. We find that there is an optimal sequence for the firm to allocate their resources: (1) build a general human capital stock before the change in the techno-economic paradigm, (2) spend on R&D, and (3) invest in specific human capital. Innovators fare better than imitators on average, not only because they innovate, but also because they build a competence base, which supports the learning from other firms.     

浅谈在职校体育课中如何加强智力的培养

体育作为一门学科，与智力有着密不可分的关系。因此本文就体育与智力的关系提出学校体育需要智力的积极参与和学校体育对智力的开发，以及职校体育教师从运动感知、运动表象、运动记忆、启发方面入手加强智力的培养。     

Cournot competition and endogenous firm size

The paper studies the dynamics of firm size in a repeated Cournot game with unknown demand function. We model the firm as a type of artificial neural network. Each period it must learn to map environmental signals to both a demand parameter and its rival’s output choice. However, this learning game is in the background, as we focus on the endogenous adjustment of network size. We investigate the long-run evolution of firm/network size as a function of profits, rival’s size, and the type of adjustment rules used.

On designing economic agents that behave like human agents

This paper explores the idea of constructing theoretical economic agents that behave like actual human agents and using them in neoclassical economic models. It does this in a repeated-choice setting by postulating artificial agents who use a learning algorithm calibrated against human learning data from psychological experiments. The resulting calibrated algorithm appears to replicate human learning behavior to a high degree and reproduces several stylized facts of learning. It can therefore be used to replace the idealized, perfectly rational agents in appropriate neoclassical models with calibrated agents that represent actual human behavior. The paper discusses the possibilities of using the algorithm to represent human learning in normal-form stage games and in more general neoclassical models in economics. It explores the likelihood of convergence to long-run optimality and to Nash behavior, and the characteristic learning time implicit in human adaptation in the economy.     

基于机器学习的专利质量评价研究

随着专利数量的迅猛增长，专利质量问题日益凸显，专利质量评价成为学者关注焦点。面对海量专利数据，如何构建有效的专利质量评价方法，实现对专利质量的准确评价和分类是一项急迫的工作。首先，通过对国内外相关专利质量评价研究进行系统调研和梳理，提出一种新的专利质量评价指标体系；其次，根据新的专利质量评价指标体系，构建一种基于机器学习的专利质量评价方法；最后，以人工智能技术专利为例进行实证研究。结果表明，有效综合利用专利技术性、经济性、法定性和主体性评价指标，有助于更加全面、深入地评价专利质量；基于机器学习的专利质量评价方法能够迅速对专利进行分类并识别高质量专利，从而提高专利质量评价结果深度，为实现大规模专利质量分类评价智能化提供可能。     

基于SOFM网络的城镇土地定级研究——以深圳宝安区为例

本文运用人工神经网络(ANN)的理论与方法,构建了应用于城镇土地定级的SOFM网络模型,将"聚类"思想应用于定级评价中,克服了传统方法因子权重过于主观的缺点。本文以深圳市宝安区为例进行了方法验证,并与传统方法进行了比较,结果表明,基于SOFM的定级模型在空间聚合性和准确性方面优化了定级结果,进一步表明了此类人工智能类方法在评价领域的适应性。     

坚持创造性智力技能培养方向走特色育才之路

高等职业技术教育大都是针对高技术职业岗位的，在这些岗位智能内涵的组成中，创造性智力技术占有较大的比重，本文总结了计算机系统在学生创造智力技能培养方面的一些认识和做法。以供同行借鉴。     

Intelligence, Human Capital, and Economic Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach

Human capital plays an important role in the theory of economic growth, but it has been difficult to measure this abstract concept. We survey the psychological literature on cross-cultural IQ tests and conclude that intelligence tests provide one useful measure of human capital. Using a new database of national average IQ, we show that in growth regressions that include only robust control variables, IQ is statistically significant in 99.8% of these 1330 regressions, easily passing a Bayesian model-averaging robustness test. A 1 point increase in a nation’s average IQ is associated with a persistent 0.11% annual increase in GDP per capita.     

我国智力资本投资决策研究

对智力资本职能重新定义,指出智力资本具有物质、精神、政策等职能,通过对中央政府、地方政府、个体对智力资本投资决策建模分析,得出中央可以根据地方偏好、个体投资实际能力,通过政府补贴引导多渠道的智力资本投资.     

人工智能时代专利制度的实践挑战与应对策略

人工智能系统日益提高的复杂度、自主决策能力,以及在更广泛领域的应用,已经对现行法律制度和监管体系构成重大挑战。特别是在专利等知识产权领域,从技术方案到创造性审查,从辅助决策到自主发明创造,整个生态系统都面临前所未有的挑战。侧重从实践角度探寻解决人工智能与专利制度冲突的手段和途径,首先,阐述现阶段人工智能专利制度的实践特征;然后,着重从人工智能的技术、应用两个层面梳理、分析和探讨实践中面临的困境与挑战;最后,结合相关专利制度、规则、程序提出针对性的应对策略和建议。