Supervisory control of a class of discrete event processes
SIAM Journal on Control and Optimization
Matrix analysis and applied linear algebra
Matrix analysis and applied linear algebra
Introduction to algorithms
On Liveness and Controlled Siphons in Petri Nets
Proceedings of the 17th International Conference on Application and Theory of Petri Nets
Near-Optimal Online Control of Dynamic Discrete-Event Systems
Discrete Event Dynamic Systems
Introduction to Discrete Event Systems
Introduction to Discrete Event Systems
Finding the Growth Rate of a Regular of Context-Free Language in Polynomial Time
DLT '08 Proceedings of the 12th international conference on Developments in Language Theory
Choice-point nets: a discrete-event modelling technique for analyzing health care protocols
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Concurrency control generation for dynamic threads using discrete-event systems
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
The SPIN Model Checker: Primer and Reference Manual
The SPIN Model Checker: Primer and Reference Manual
Extension based Limited Lookahead Supervision of Discrete Event Systems
Automatica (Journal of IFAC)
Concurrency control generation for dynamic threads using discrete-event systems
Science of Computer Programming
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Limited lookahead supervision is a discrete-event systems framework in which control decisions are made by looking at finite-step projections of the behaviour of the system's underlying automata. Projected system behaviour is represented as a lookahead tree with some depth limit decided on by the user. It can be difficult to strike a balance between the complexities associated with storing and analyzing the trees and the amount of information available to make decisions, both of which increase with depth. This paper considers the problem of accurately estimating the state space of lookahead trees with the intent of simplifying the process of determining a favourable depth to use. Although the estimation methods presented here apply cleanly to only certain kinds of automata, they also shed light onto the more complex behaviour of the others.