54 search results - page 3 / 11 » Convergence Results for Single-Step On-Policy Reinforcement-... |
IJCAI
2001
13 years 7 months ago
2001
Most formulations of Reinforcement Learning depend on a single reinforcement reward value to guide the search for the optimal policy solution. If observation of this reward is rar...
AAMAS
2007
Springer
14 years 10 days ago
2007
Springer
Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
ICML
2007
IEEE
14 years 7 months ago
2007
IEEE
Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...
CORR
2012
Springer
12 years 1 months ago
2012
Springer
Reinforcement learning addresses the dilemma between exploration to find profitable actions and exploitation to act according to the best observations already made. Bandit proble...
SIAMCO
2000
13 years 6 months ago
2000
It is shown here that stability of the stochastic approximation algorithm is implied by the asymptotic stability of the origin for an associated ODE. This in turn implies convergen...