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ICML
2009
IEEE
15 years 10 months ago
Binary action search for learning continuous-action control policies
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
Jason Pazis, Michail G. Lagoudakis
HYBRID
2000
Springer
15 years 1 months ago
A Hybrid Feedback Regulator Approach to Control an Automotive Suspension System
Abstract. In this paper, we demonstrate a novel hybrid control synthesis approach using an automotive suspension system. Discrete abstractions are used to approximate the continuou...
Xenofon D. Koutsoukos, Panos J. Antsaklis
ECAI
2010
Springer
14 years 11 months ago
The Dynamics of Multi-Agent Reinforcement Learning
Abstract. Infinite-horizon multi-agent control processes with nondeterminism and partial state knowledge have particularly interesting properties with respect to adaptive control, ...
Luke Dickens, Krysia Broda, Alessandra Russo
MANSCI
2011
14 years 25 days ago
Dynamic Price Competition with Fixed Capacities
Many revenue management (RM) industries are characterized by (a) fixed capacities in the short term (e.g., hotel rooms, seats on an airline flight), (b) homogeneous products (e....
Victor Martínez-de-Albéniz, Kalyan T...
AMAI
2008
Springer
14 years 10 months ago
Bayesian learning of Bayesian networks with informative priors
This paper presents and evaluates an approach to Bayesian model averaging where the models are Bayesian nets (BNs). Prior distributions are defined using stochastic logic programs...
Nicos Angelopoulos, James Cussens