1233 search results - page 67 / 247 » Reinforcement learning |
113
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NIPS
1993
15 years 2 months ago
1993
While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
136
Voted
AI
1999
Springer
15 years 12 days ago
1999
Springer
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...
105
Voted
VLSID
2005
IEEE
15 years 6 months ago
2005
IEEE
The primary advantage of using 3D-FPGA over 2D-FPGA is that the vertical stacking of active layers reduce the Manhattan distance between the components in 3D-FPGA than when placed...
75
Voted
PRICAI
1999
Springer
15 years 5 months ago
1999
Springer
Abstract. In multi-agent reinforcement learning systems, it is important to share a reward among all agents. We focus on the Rationality Theorem of Profit Sharing [5] and analyze ...
95
Voted
NIPS
1994
15 years 2 months ago
1994
It is widely accepted that the use of more compact representations than lookup tables is crucial to scaling reinforcement learning (RL) algorithms to real-world problems. Unfortun...