311 search results - page 3 / 63 » Learning first-order probabilistic models with combining rul... |
CEC
2003
IEEE
15 years 1 months ago
2003
IEEE
- As an alternative to traditional Evolutionary Algorithms (EAs), Population-Based Incremental Learning (PBIL) maintains a probabilistic model of the best individual(s). Originally...
ACL
1998
14 years 11 months ago
1998
In this paper we present the results of the combination of stochastic and rule-based disambiguation methods applied to Basque languagel. The methods we have used in disambiguation...
KR
2004
Springer
15 years 2 months ago
2004
Springer
To learn to behave in highly complex domains, agents must represent and learn compact models of the world dynamics. In this paper, we present an algorithm for learning probabilist...
DAGSTUHL
2007
14 years 11 months ago
2007
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
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ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
Inference in graphical models has emerged as a promising technique for planning. A recent approach to decision-theoretic planning in relational domains uses forward inference in d...