搜索资源列表
pomdp1
- 求解POMDP问题的一个重要方法，对策略空间进行简化-We propose a new approach to the problem of searching a space of policies for a Markov decision process (MDP) or a partially observable Markov decision process (POMDP), given a model.
QoS-of-markov-selection-strategy
- 面向QOS的马尔可夫选择决策算法，通过对算法模型合理化构建过程于异构环境特点的紧密结合，最大程度满足异构网络环境中用户QOS的长期效益-Facing the QOS markov selection decision algorithm, based on the rationalization process in constructing algorithm model heterogeneous environment characteristics of closely, satisfy
Optimality-of-the-NVI-Adaptive-Policy-for-a-Parti
- Paper on the optimality of a non-stationary value iteration adaptive policy for a Partially Observed Markov Decision Proce-Paper on the optimality of a non-stationary value iteration adaptive policy for a Partially Observed Markov Decision Process
On the Computation of the Optimal cost Function for Discrete Markov Models with Partial Observations
- Analytical solution for 2-dimensional partially observable Markov Decision Processes.
Optimal Cost and Policy for a Markovian Replacement Problem
- Partially Observable Markov decision model for a replacement/inventory problem. Cost is solved in closed form.
2012.李航.统计学习方法
- 《统计学习方法》是计算机及其应用领域的一门重要的学科。《统计学习方法》全面系统地介绍了统计学习的主要方法，特别是监督学习方法，包括感知机、k近邻法、朴素贝叶斯法、决策树、逻辑斯谛回归与最大熵模型、支持向量机、提升方法、EM算法、隐马尔可夫模型和条件随机场等。除第1章概论和最后一章总结外，每章介绍一种方法。叙述从具体问题或实例入手，由浅入深，阐明思路，给出必要的数学推导，便于读者掌握统计学习方法的实质，学会运用。为满足读者进一步学习的需要，书中还介绍了一些相关研究，给出了少量习题，列出了主要参考文