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ISIPTA
2005
IEEE
140views Mathematics» more  ISIPTA 2005»
15 years 3 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
14 years 10 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
14 years 10 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 1 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
13 years 9 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