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» Algorithms for Inverse Reinforcement Learning
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ICML
1994
IEEE
14 years 1 months ago
Markov Games as a Framework for Multi-Agent Reinforcement Learning
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....
Michael L. Littman
IJRR
2008
151views more  IJRR 2008»
13 years 10 months ago
Trajectory Optimization using Reinforcement Learning for Map Exploration
Automatically building maps from sensor data is a necessary and fundamental skill for mobile robots; as a result, considerable research attention has focused on the technical chall...
Thomas Kollar, Nicholas Roy
AROBOTS
1999
104views more  AROBOTS 1999»
13 years 9 months ago
Reinforcement Learning Soccer Teams with Incomplete World Models
We use reinforcement learning (RL) to compute strategies for multiagent soccer teams. RL may pro t signi cantly from world models (WMs) estimating state transition probabilities an...
Marco Wiering, Rafal Salustowicz, Jürgen Schm...
KES
2007
Springer
14 years 4 months ago
Making Financial Trading by Recurrent Reinforcement Learning
In this paper we propose a financial trading system whose strategy is developed by means of an artificial neural network approach based on a recurrent reinforcement learning algo...
Francesco Bertoluzzo, Marco Corazza
ICRA
2006
IEEE
161views Robotics» more  ICRA 2006»
14 years 4 months ago
Quadruped Robot Obstacle Negotiation via Reinforcement Learning
— Legged robots can, in principle, traverse a large variety of obstacles and terrains. In this paper, we describe a successful application of reinforcement learning to the proble...
Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Sin...