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ISIPTA
2005
IEEE
140views Mathematics» more  ISIPTA 2005»
15 years 6 months ago
Conservative Rules for Predictive Inference with Incomplete Data
This paper addresses the following question: how should we update our beliefs after observing some incomplete data, in order to make credible predictions about new, and possibly i...
Marco Zaffalon
NIPS
1998
15 years 2 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore
AAAI
2000
15 years 2 months ago
A Consistency-Based Model for Belief Change: Preliminary Report
We present a general, consistency-based framework for belief change. Informally, in revising K by , we begin with and incorporate as much of K as consistently possible. Formally, ...
James P. Delgrande, Torsten Schaub
ECAI
1992
Springer
15 years 5 months ago
A Strategy for the Computation of Conditional Answers
We consider non-Horn Deductive Data Bases (DDB) represented in a First Order language without function symbols. In this context the DDB is an incomplete description of the world. ...
Robert Demolombe
ATAL
2011
Springer
14 years 1 months ago
Information elicitation for decision making
Proper scoring rules, particularly when used as the basis for a prediction market, are powerful tools for eliciting and aggregating beliefs about events such as the likely outcome...
Yiling Chen, Ian A. Kash