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UAI
1998
13 years 9 months ago
A Multivariate Discretization Method for Learning Bayesian Networks from Mixed Data
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
Stefano Monti, Gregory F. Cooper
ECML
2004
Springer
14 years 1 months ago
Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics
In this paper, we show how the dynamics of Q-learning can be visualized and analyzed from a perspective of Evolutionary Dynamics (ED). More specifically, we show how ED can be use...
Pieter Jan't Hoen, Karl Tuyls
SEKE
2007
Springer
14 years 1 months ago
Adjudicator: A Statistical Approach for Learning Ontology Concepts from Peer Agents
— We present a statistical approach for software agents to learn ontology concepts from peer agents by asking them whether they can reach consensus on significant differences bet...
Behrouz Homayoun Far, Abdel Halim Elamy, Nora Houa...
AAAI
2000
13 years 9 months ago
Restricted Bayes Optimal Classifiers
We introduce the notion of restricted Bayes optimal classifiers. These classifiers attempt to combine the flexibility of the generative approach to classification with the high ac...
Simon Tong, Daphne Koller
ICRA
2006
IEEE
104views Robotics» more  ICRA 2006»
14 years 1 months ago
Implicit Coordination in Robotic Teams using Learned Prediction Models
— Many application tasks require the cooperation of two or more robots. Humans are good at cooperation in shared workspaces, because they anticipate and adapt to the intentions a...
Freek Stulp, Michael Isik, Michael Beetz