250 search results - page 16 / 50 » Learning action effects in partially observable domains |
AI
1998
Springer
15 years 1 months ago
1998
Springer
This paper presents and evaluates sequential instance-based learning (SIBL), an approach to action selection based upon data gleaned from prior problem solving experiences. SIBL le...
105
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SAC
2005
ACM
15 years 3 months ago
2005
ACM
This paper presents a novel model of reinforcement learning agents. A feature of our learning agent model is to integrate analytic hierarchy process (AHP) into a standard reinforc...
CLEIEJ
2008
14 years 9 months ago
2008
In the past few years Artificial Intelligence has been gradually introduced to enhance Education through technologies. However, usual approaches provide systems with a kind of exp...
ICMLA
2010
14 years 7 months ago
2010
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
94
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ATAL
2011
Springer
13 years 9 months ago
2011
Springer
In multi-agent planning environments, action models for each agent must be given as input. However, creating such action models by hand is difficult and time-consuming, because i...