摘要翻译：
在少数、多数和美元游戏(MG、MAGG、$G)中，合成代理人在每一个时间阶段都按照他们有限的策略中先前表现最好的策略进行竞争以获得奖励。这些游戏模拟了现实世界金融市场的不同组成部分和/或方面。在MG中，代理人争夺稀缺资源；在群体中，男人们模仿群体，希望开拓一种趋势；在$g中，代理试图成功地预测市场的趋势和变化，并从中受益。以前的研究表明，在平衡之前的一个合理数量的初步时间步骤（时间范围MG,THMG）中，代理人试图通过主动的策略选择来优化他们的收益是“虚幻的”：计算出的他们个人策略的假设收益平均大于代理人的实际平均收益。此外，如果一小部分代理有意选择并按照其看似最差的策略行事，这些代理平均超过所有其他代理，甚至获得平均正收益，否则MG中的代理很少。后一种现象提出了优化程序在MAJG和$G中的效果如何的问题。我们证明了在MAJG和$G中不存在控制幻觉。换句话说，低熵（信息更丰富）策略在MG中的表现低于高熵（或随机）策略，但在MAGG和$G中的表现优于高熵（或随机）策略。这进一步澄清了在先验定义的设置中受到真正控制的情况，以及那些不受控制的情况，以强调优化的重要性。
---
英文标题：
《Illusory versus Genuine Control in Agent-Based Games》
---
作者：
J.B. Satinover and D. Sornette
---
最新提交年份：
2008
---
分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Trading and Market Microstructure        交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
--
一级分类：Physics        物理学
二级分类：Adaptation and Self-Organizing Systems        自适应和自组织系统
分类描述：Adaptation, self-organizing systems, statistical physics, fluctuating systems, stochastic processes, interacting particle systems, machine learning
自适应，自组织系统，统计物理，波动系统，随机过程，相互作用粒子系统，机器学习
--

---
英文摘要：
  In the Minority, Majority and Dollar Games (MG, MAJG, $G), synthetic agents compete for rewards, at each time-step acting in accord with the previously best-performing of their limited sets of strategies. Different components and/or aspects of real-world financial markets are modelled by these games. In the MG, agents compete for scarce resources; in the MAJG gents imitate the group in the hope of exploiting a trend; in the $G agents attempt to successfully predict and benefit from trends as well as changes in the direction of a market. It has been previously shown that in the MG for a reasonable number of preliminary time steps preceding equilibrium (Time Horizon MG, THMG), agents' attempt to optimize their gains by active strategy selection is ``illusory'': The calculated hypothetical gains of their individual strategies is greater on average than agents' actual average gains. Furthermore, if a small proportion of agents deliberately choose and act in accord with their seemingly worst performing strategy, these outper-form all other agents on average, and even attain mean positive gain, otherwise rare for agents in the MG. This latter phenomenon raises the question as to how well the optimization procedure works in the MAJG and $G. We demonstrate that the illusion of control is absent in MAJG and $G. In other words, low-entropy (more informative) strategies under-perform high-entropy (or random) strategies in the MG but outperform them in the MAJG and $G. This provides further clarification of the kinds of situations subject to genuine control, and those not, in set-ups a priori defined to emphasize the importance of optimization.
---
PDF链接：
https://arxiv.org/pdf/0802.4165