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SGAI
2004
Springer
16 years 1 days ago
Interactive Selection of Visual Features through Reinforcement Learning
We introduce a new class of Reinforcement Learning algorithms designed to operate in perceptual spaces containing images. They work by classifying the percepts using a computer vi...
Sébastien Jodogne, Justus H. Piater
AGENTS
2001
Springer
15 years 11 months ago
Learning structured reactive navigation plans from executing MDP navigation policies
Autonomous robots, such as robot office couriers, need navigation routines that support flexible task execution and effective action planning. This paper describes XFRMLEARN, a s...
Michael Beetz, Thorsten Belker
AAAI
2008
15 years 9 months ago
Learning to Connect Language and Perception
To truly understand language, an intelligent system must be able to connect words, phrases, and sentences to its perception of objects and events in the world. Current natural lan...
Raymond J. Mooney
AAAI
2007
15 years 9 months ago
RETALIATE: Learning Winning Policies in First-Person Shooter Games
In this paper we present RETALIATE, an online reinforcement learning algorithm for developing winning policies in team firstperson shooter games. RETALIATE has three crucial chara...
Megan Smith, Stephen Lee-Urban, Hector Muño...
AAAI
1996
15 years 8 months ago
Generation of Attributes for Learning Algorithms
Inductive algorithms rely strongly on their representational biases, Constructive induction can mitigate representational inadequacies. This paper introduces the notion of a relat...
Yuh-Jyh Hu, Dennis F. Kibler