Algorithms for Sequential Decision Making - Littman - 1996 () Citation Context ... that have linguistic similarities. We propose to capture the HMM’s complexity and its associated CHAPTER 1: INTRODUCTION 2 interrelationships in a richer, more general model: a POMDP [Whi80] [Che88] =-=[Lit...
Sequential Problems State Uncertainty Collaborative Agents Appendices A: Mathematical Concepts B: Probability Distributions C: Computational Complexity D: Neural Representations E: Search Algorithms F: Problems G: Julia 【斯坦福新书】决策算法,464页pdf,Algorithms for Decision Makingwww.zhuanzhi.ai/vip/01...
In data science, researchers typically deal with data that contain noisy observations. An important problem explored by data scientists in this context is the problem of sequential decision making. This is commonly known as a "stochastic multi-armed bandit"(stochastic MAB). Here, an intelligent age...
Dynamic Programming (DP): DP is an optimization technique that is used to solve problems that can be broken down into smaller subproblems. It is particularly useful for problems that involve sequential decision-making, such as scheduling energy storage systems or optimizing the operation of a micro...
The MDP (Chang et al. [14], Panigrahi and Bhatnagar [8,9]) has been introduced to model hierarchical decision making problems. Chang et al. [14] propose a model called the multi-time scale Markov decision process (MMDP) for hierarchically structured sequential decision making processes. Show...
In all of these scenarios, the simultaneity of the decision-making is crucial and we have to include it directly into the model when computing strategies. One of the fundamental differences of simultaneous move games versus strictly sequential games is that the agents may need to use randomized ...
(1990). Learning and sequential decision making. In: M. Gabriel & J.W. Moore (Eds.),Learning and computational neuroscience: Foundations of adaptive networks. Cambridge, MA: MIT Press. Google Scholar Dayan, P. (1990). Reinforcement comparison. In D.S. Touretzky, J.L. Elman, T.J. ...
Representation Matters: Offline Pretraining for Sequential Decision Making Mengjiao Yang and Ofir Nachum. ICML, 2021. Offline Reinforcement Learning with Pseudometric Learning Robert Dadashi, Shideh Rezaeifar, Nino Vieillard, Léonard Hussenot, Olivier Pietquin, and Matthieu Geist. ICML, 2021. Au...
It includes new material on sequential structure, searching and priority search trees. The Algorithm Design Manual (Steven S. Skiena) This book serves as the primary textbook for any algorithm design course while maintaining its status as the premier practical reference guide to algorithms, ...
In many sequential decision-making problems we may want to manage risk by minimizing some measure of variability in rewards in addition to maximizing a standard criterion. Variance-related risk measures are among the most common risk-sensitive criteria in finance and operations research. However, ...