4446 search results - page 194 / 890 » Learning Observer Agents |
118
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COLT
1993
Springer
15 years 8 months ago
1993
Springer
We introduce a new formal model in which a learning algorithm must combine a collection of potentially poor but statistically independent hypothesis functions in order to approxima...
161
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HICSS
2003
IEEE
15 years 9 months ago
2003
IEEE
This paper uses partially observable Markov decision processes (POMDP’s) as a basic framework for MultiAgent planning. We distinguish three perspectives: first one is that of a...
134
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FLAIRS
2001
15 years 5 months ago
2001
This paper presents a probabilistic and abductive theory of plan recognition that handles agents that are actively hostile to the inference of their plans. This focus violates a p...
115
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ICONIP
2007
15 years 5 months ago
2007
One of the authors has proposed a simple learning algorithm for recurrent neural networks, which requires computational cost and memory capacity in practical order O(n2 )[1]. The a...
115
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SDM
2004
SIAM
15 years 5 months ago
2004
SIAM
We present a novel probabilistic multiple cause model for binary observations. In contrast to other approaches, the model is linear and it infers reasons behind both observed and ...