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WSC
2007
13 years 6 months ago
Optimizing time warp simulation with reinforcement learning techniques
Adaptive Time Warp protocols in the literature are usually based on a pre-defined analytic model of the system, expressed as a closed form function that maps system state to cont...
Jun Wang, Carl Tropper
WSC
1998
13 years 5 months ago
Combining Optimism Limiting Schemes in Time Warp Based Parallel Simulations
The Time Warp protocol is considered to be an effective synchronization mechanism for parallel discrete event simulation (PDES). However, it is widely recognized that it suffers o...
Kevin G. Jones, Samir Ranjan Das
DSRT
2008
IEEE
13 years 6 months ago
Lightweight Time Warp - A Novel Protocol for Parallel Optimistic Simulation of Large-Scale DEVS and Cell-DEVS Models
This paper proposes a novel Lightweight Time Warp (LTW) protocol for high-performance parallel optimistic simulation of large-scale DEVS and CellDEVS models. By exploiting the cha...
Qi Liu, Gabriel A. Wainer
FLAIRS
2010
13 years 2 months ago
Decision-Theoretic Simulated Annealing
The choice of a good annealing schedule is necessary for good performance of simulated annealing for combinatorial optimization problems. In this paper, we pose the simulated anne...
Todd W. Neller, Christopher J. La Pilla
NIPS
2001
13 years 5 months ago
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...