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233views
14 years 2 months ago
Sparse reward processes
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
Christos Dimitrakakis
ICRA
2009
IEEE
227views Robotics» more  ICRA 2009»
15 years 10 months ago
Adaptive autonomous control using online value iteration with gaussian processes
— In this paper, we present a novel approach to controlling a robotic system online from scratch based on the reinforcement learning principle. In contrast to other approaches, o...
Axel Rottmann, Wolfram Burgard
ICML
1994
IEEE
15 years 7 months ago
Learning Without State-Estimation in Partially Observable Markovian Decision Processes
Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...
ICCBR
2005
Springer
15 years 9 months ago
Opportunities for CBR in Learning by Doing
In this paper we partially describe JV2 M, a metaphorical simulation of the Java Virtual Machine where students can learn Java language compilation and reinforce object-oriented pr...
Pedro Pablo Gómez-Martín, Marco Anto...
FLAIRS
2000
15 years 5 months ago
Resolving Conflicts Among Actions in Concurrent Behaviors
A robotic agent must coordinate its coupled concurrent behaviors to produce a coherent response to stimuli. Reinforcement learning has been used extensively in coordinating sensin...
Henry Hexmoor