Controlled stochastic systems occur in science engineering, manufacturing, social sciences,
and many other cntexts. If the systems is modeled as a Markov decision process (MDP) and …

This work surveys results on the complexity of planning under uncertainty. The planning
model considered is the partially-observable Markov decision process. The general …

This paper presents a Q-learning approach to state-based planning of behaviour-based
walking robots. The learning process consists of a teaching stage and an autonomous …

Mobile robot localization is the problem of determining a robot's pose from sensor data. This
thesis presents a family of probabilistic localization algorithms known as Monte Carlo …

Many two layer robot architectures have been proposed and implemented. While
justification for the design can be well argued, how does one know it is really a good idea …

Abstract Markov Decision Process (MDP) has enormous applications in science,
engineering, economics and management. Most of decision processes have Markov …

Since the 1970s, the National Aeronautics and Space Administration (NASA) has been
conducting experiments to improve the duration and safety of manned space missions. For …

فرآیند تصمیم گیری مارکوف یا MDP, یکی از مسایلی است که دارای کاربردهای وسیعی در زمینه
های مختلف علمی, مهندسی, اقتصادی و مدیریت است. بسیاری از فرآیندهای تصمیم گیری, دارای …‎

Abstract Partially Observable Markov Decision Processes (POMDPs) have been applied
extensively to planning in environments where knowledge of an underlying process is …

Localization, that is the estimation of a robot's location from sensor data, is a fundamental
problem in mobile robotics. This thesis presents a version of Markov Localization that …