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ICML
2005
IEEE
15 years 11 months ago
Bayesian sparse sampling for on-line reward optimization
We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...
FROCOS
2011
Springer
13 years 9 months ago
Stochastic Local Search for SMT: Combining Theory Solvers with WalkSAT
A dominant approach to Satisfiability Modulo Theories (SMT) relies on the integration of a Conflict-Driven-Clause-Learning (CDCL) SAT solver and of a decision procedure able to h...
Alberto Griggio, Quoc-Sang Phan, Roberto Sebastian...
SASO
2009
IEEE
15 years 4 months ago
Distributed W-Learning: Multi-Policy Optimization in Self-Organizing Systems
—Large-scale agent-based systems are required to self-optimize towards multiple, potentially conflicting, policies of varying spatial and temporal scope. As a result, not all ag...
Ivana Dusparic, Vinny Cahill
AAAI
2010
14 years 11 months ago
Online Learning of Uneven Terrain for Humanoid Bipedal Walking
We present a novel method to control a biped humanoid robot to walk on unknown inclined terrains, using an online learning algorithm to estimate in real-time the local terrain fro...
Seung-Joon Yi, Byoung-Tak Zhang, Daniel D. Lee
ATAL
2009
Springer
15 years 4 months ago
Solving multiagent assignment Markov decision processes
We consider the setting of multiple collaborative agents trying to complete a set of tasks as assigned by a centralized controller. We propose a scalable method called“Assignmen...
Scott Proper, Prasad Tadepalli