CIF: Small: Controlling Uncertainty: On the Sequential Refinement of Belief

控制不确定性：关于信念的顺序细化本研究集中在各种信息获取和传感应用中，决策者通过仔细控制一系列具有不确定结果的行动，以快速，准确和有效的方式动态地细化他对感兴趣现象的信念。该模型包括通信，实验设计，认知科学和传感器管理中的一类应用。特别是，以下三个问题得到解决。主动序贯假设检验：有一组假设，其中一个是真的。决策者被要求通过顺序地采用任何一个可用的传感动作来识别正确的假设。行动的成本不同，并产生统计上的差异。在给定声明错误惩罚的情况下，研究了感知动作的最优选择问题.带带宽扩展的信源信道联合编码的反馈方案：通过带反馈的无记忆噪声信道将消息传送到接收机。信息和接收者之间的预期失真？的建设是寻求最小化的因果编码功能的选择以及解码功能。联合信源信道编码在多址接入信道与反馈：多个发射机传递消息到一个共同的接收机在一个嘈杂的无记忆多址信道与完美的输出反馈。这些问题归结为一个动态系统的顺序控制，其系统是未知（真假设，消息等）的一致性分布，其动态是由贝叶斯？统治特别是，最佳选择的行动，即细化在theconnestal分布和减少的不确定性，进行了研究。

Controlling Uncertainty: On the Sequential Refinement of BeliefThis research focuses on a variety of information acquisition and sensing applications in which adecision maker, by carefully controlling a sequence of actions with uncertain outcomes,dynamically refines his belief about a phenomenon of interest in a speedy, accurate, and efficientmanner. The model includes a class of applications in communications, design of experiments,cognitive science, and sensor management. In particular, the following three problems aretackled.? Active Sequential Hypothesis Testing: There are a set of hypotheses, one of which is true. Adecision maker is asked to identify the correct hypothesis by sequentially employing either oneof available sensing actions. Actions costs differently and produce statistically distinctobservations. Given a penalty for error in declaration, the work investigates the optimalselection of sensing actions.? Feedback Schemes for Joint Source-Channel Coding with Bandwidth Expansion: A message isto be conveyed to a receiver over a noisy memoryless channel with feedback. The expecteddistortion between the message and the receiver?s construction is sought to be minimized overthe choice of causal encoding functions as well as the decoding function.? Joint Source-Channel Coding over a Multiple Access Channel with Feedback: Multipletransmitters convey messages to a common receiver over a noisy memoryless multiple accesschannel with perfect output feedback.These problems boil down to the sequential control of a dynamical system whose system is theconditional distribution of the unknown (true hypothesis, message, etc) and whose dynamics isdictated by the Bayes? rule. In particular, the optimal choice of actions, i.e. refinement in theconditional distribution and reduction of uncertainty, is investigated.