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71
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ICML
1995
IEEE
15 years 29 days ago
Learning with Rare Cases and Small Disjuncts
Systems that learn from examples often create a disjunctive concept definition. Small disjuncts are those disjuncts which cover only a few training examples. The problem with sma...
Gary M. Weiss
83
Voted
ICML
1995
IEEE
15 years 10 months ago
Learning by Observation and Practice: An Incremental Approach for Planning Operator Acquisition
This paper describes an approach to automatically learn planning operators by observing expert solution traces and to further refine the operators through practice in a learning-b...
Xuemei Wang
ICML
1995
IEEE
15 years 10 months ago
Ant-Q: A Reinforcement Learning Approach to the Traveling Salesman Problem
In this paper we introduce Ant-Q, a family of algorithms which present many similarities with Q-learning (Watkins, 1989), and which we apply to the solution of symmetric and asymm...
Luca Maria Gambardella, Marco Dorigo
108
Voted
ICML
1995
IEEE
15 years 10 months ago
Learning Policies for Partially Observable Environments: Scaling Up
Partially observable Markov decision processes (pomdp's) model decision problems in which an agent tries to maximize its reward in the face of limited and/or noisy sensor fee...
Michael L. Littman, Anthony R. Cassandra, Leslie P...
88
Voted
ICML
2001
IEEE
15 years 10 months ago
Off-Policy Temporal Difference Learning with Function Approximation
We introduce the first algorithm for off-policy temporal-difference learning that is stable with linear function approximation. Off-policy learning is of interest because it forms...
Doina Precup, Richard S. Sutton, Sanjoy Dasgupta