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ICML
2000
IEEE
14 years 9 months ago
Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots
Decision-theoretic reasoning and planning algorithms are increasingly being used for mobile robot navigation, due to the signi cant uncertainty accompanying the robots' perce...
Daniel Nikovski, Illah R. Nourbakhsh
NIPS
2003
13 years 10 months ago
An MCMC-Based Method of Comparing Connectionist Models in Cognitive Science
Despite the popularity of connectionist models in cognitive science, their performance can often be difficult to evaluate. Inspired by the geometric approach to statistical model ...
Woojae Kim, Daniel J. Navarro, Mark A. Pitt, In Ja...
ATAL
2006
Springer
14 years 13 days ago
Rule value reinforcement learning for cognitive agents
RVRL (Rule Value Reinforcement Learning) is a new algorithm which extends an existing learning framework that models the environment of a situated agent using a probabilistic rule...
Christopher Child, Kostas Stathis
NIPS
2003
13 years 10 months ago
From Algorithmic to Subjective Randomness
We explore the phenomena of subjective randomness as a case study in understanding how people discover structure embedded in noise. We present a rational account of randomness per...
Thomas L. Griffiths, Joshua B. Tenenbaum
ALT
2004
Springer
14 years 5 months ago
New Revision Algorithms
A revision algorithm is a learning algorithm that identifies the target concept, starting from an initial concept. Such an algorithm is considered efficient if its complexity (in ...
Judy Goldsmith, Robert H. Sloan, Balázs Sz&...