Learning a Partially-Known Discrete Event System
نویسندگان
چکیده
منابع مشابه
Reinforcement Learning with Partially Known World Dynamics
Reinforcement learning would enjoy better success on real-world problems if domain knowledge could be imparted to the algorithm by the modelers. Most problems have both hidden state and unknown dynamics. Partially observable Markov decision processes (POMDPs) allow for the modeling of both. Unfortunately, they do not provide a natural framework in which to specify knowledge about the domain dyn...
متن کاملPredictability of event occurrences in partially-observed discrete-event systems
This paper studies the problem of predicting occurrences of a significant event in a partially-observed discrete-event system. The predictability of occurrences of an event in a system is defined in the context of formal languages. The predictability of a language is a stronger condition than the diagnosability of the language. Two necessary and sufficient conditions for predictability of occur...
متن کاملTime Management Approach on a Discrete Event Manufacturing System Modeled by Petri Net
Discrete event system, Supervisory control, Petri Net, Constraint This paper presents a method to manage the time in a manufacturing system for obtaining an optimized model. The system in this paper is modeled by the timed Petri net and the optimization is performed based on the structural properties of Petri nets. In a system there are some states which are called forbidden states an...
متن کاملA language measure for partially observed discrete event systems
Recent literature has introduced and validated a signed real measure of regular languages for quantitative analysis and synthesis of discrete-event supervisory (DES) control systems, where all events are assumed to be observable. This paper presents a modification of the language measure for supervisory control under partial observation and shows how to generalize the analysis when some of the ...
متن کاملSupervisory control of partially observed discrete event systems based on a reinforcement learning
In discrete event systems, the supervisor controls events to satisfy the control specifications given by formal languages. However a precise description of the specifications and the discrete event systems is required for constructing the supervisor. So, this paper proposes a method to construct a supervisor based on a reinforcement learning for partially observed discrete event systems. In the...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2020
ISSN: 2169-3536
DOI: 10.1109/access.2020.2983074