Near Optimal Task Graph Scheduling with Priced Timed Automata and Priced Timed Markov Decision Processes

by   Anne Ejsing, et al.

Task graph scheduling is a relevant problem in computer science with application to diverse real world domains. Task graph scheduling suffers from a combinatorial explosion and thus finding optimal schedulers is a difficult task. In this paper we present a methodology for computing near-optimal preemptive and non-preemptive schedulers for task graphs. The task graph scheduling problem is reduced to location reachability via the fastest path in Priced Timed Automata (PTA) and Priced Timed Markov Decision Processes (PTMDP). Additionally, we explore the effect of using chains to reduce the computation time for finding schedules. We have implemented our models in UPPAAL CORA and UPPAAL STRATEGO. We conduct an exhaustive experimental evaluation where we compare our resulting schedules with the best-known schedules of a state of the art tool. A significant number of our resulting schedules are shown to be shorter than or equal to the best-known schedules.


page 1

page 2

page 3

page 4


On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes

We consider infinite-horizon stationary γ-discounted Markov Decision Pro...

Taming denumerable Markov decision processes with decisiveness

Decisiveness has proven to be an elegant concept for denumerable Markov ...

Multi-weighted Markov Decision Processes with Reachability Objectives

In this paper, we are interested in the synthesis of schedulers in doubl...

Safe Learning for Near Optimal Scheduling

In this paper, we investigate the combination of synthesis techniques an...

Learning Factored Markov Decision Processes with Unawareness

Methods for learning and planning in sequential decision problems often ...

Performance Guarantees for Homomorphisms Beyond Markov Decision Processes

Most real-world problems have huge state and/or action spaces. Therefore...

Active Learning of Markov Decision Processes using Baum-Welch algorithm (Extended)

Cyber-physical systems (CPSs) are naturally modelled as reactive systems...