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IJCAI
2007
14 years 11 months ago
Bayesian Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
Deepak Ramachandran, Eyal Amir
AI
1999
Springer
14 years 9 months ago
Cooperative Behavior Acquisition for Mobile Robots in Dynamically Changing Real Worlds Via Vision-Based Reinforcement Learning a
In this paper, we first discuss the meaning of physical embodiment and the complexity of the environment in the context of multi-agent learning. We then propose a vision-based rei...
Minoru Asada, Eiji Uchibe, Koh Hosoda
ICML
2003
IEEE
15 years 10 months ago
Q-Decomposition for Reinforcement Learning Agents
The paper explores a very simple agent design method called Q-decomposition, wherein a complex agent is built from simpler subagents. Each subagent has its own reward function and...
Stuart J. Russell, Andrew Zimdars
83
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ICCV
2009
IEEE
16 years 2 months ago
Action Detection in Complex Scenes with Spatial and Temporal Ambiguities
In this paper, we investigate the detection of semantic human actions in complex scenes. Unlike conventional action recognition in well-controlled environments, action detection...
Yuxiao Hu, Liangliang Cao, Fengjun Lv, Shuicheng Y...
ATAL
2007
Springer
15 years 1 months ago
A reinforcement learning based distributed search algorithm for hierarchical peer-to-peer information retrieval systems
The dominant existing routing strategies employed in peerto-peer(P2P) based information retrieval(IR) systems are similarity-based approaches. In these approaches, agents depend o...
Haizheng Zhang, Victor R. Lesser