We consider the problem of estimation from survey data gathered from strategic and boundedly-rational agents with heterogeneous objectives and available information. Particularly, we consider a setting where there are three different types of survey responders with varying levels of available information, strategicness, and cognitive hierarchy: i) a non-strategic agent with an honest response, ii) a strategic agent that believes everyone else is a non-strategic agent and that the decoder also believes the same, hence assumes a naive estimator, i.e., level-1 in cognitive hierarchy, iii) and strategic agent that believes the population is Poisson distributed over the previous types, and that the decoder believes the same. We model each of these scenarios as a strategic classification of a 2-dimensional source (possibly correlated source and bias components) with quadratic distortion measures and provide a design algorithm. Finally, we provide our numerical results and the code to obtain them for research purposes at https://github.com/strategic-quantization/bounded-rationality.

翻译：本文研究从具有异质目标和可用信息的战略性有限理性智能体收集的调查数据进行估计的问题。具体而言，我们考虑存在三种不同类型调查响应者的场景，其可用信息水平、策略性程度和认知层级各不相同：i) 提供诚实响应的非策略性智能体；ii) 策略性智能体，其认为其他所有个体均为非策略性智能体且解码器亦持相同信念，因此采用朴素估计器（即认知层级中的第1级）；iii) 策略性智能体，其认为总体服从基于前述类型的泊松分布，且解码器亦持相同信念。我们将每种场景建模为具有二次失真度量的二维信源（可能包含相关信源与偏差分量）的策略性分类问题，并提供设计算法。最后，我们在 https://github.com/strategic-quantization/bounded-rationality 提供数值结果及用于研究目的的代码。