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PRICAI
1999
Springer
15 years 8 months ago
Rationality of Reward Sharing in Multi-agent Reinforcement Learning
Abstract. In multi-agent reinforcement learning systems, it is important to share a reward among all agents. We focus on the Rationality Theorem of Profit Sharing [5] and analyze ...
Kazuteru Miyazaki, Shigenobu Kobayashi
140
Voted
ICCBR
2010
Springer
15 years 8 months ago
Reducing the Memory Footprint of Temporal Difference Learning over Finitely Many States by Using Case-Based Generalization
In this paper we present an approach for reducing the memory footprint requirement of temporal difference methods in which the set of states is finite. We use case-based generaliza...
Matt Dilts, Héctor Muñoz-Avila
ATAL
2006
Springer
15 years 8 months ago
Learning executable agent behaviors from observation
We present a method for learning a human understandable, executable model of an agent's behavior using observations of its interaction with the environment. By executable we ...
Andrew Guillory, Hai Nguyen, Tucker R. Balch, Char...
EPIA
1995
Springer
15 years 8 months ago
Using Stochastic Grammars to Learn Robotic Tasks
Abstract. The paper introduces a reinforcement learning-based methodology for performance improvement of Intelligent Controllers. The translation interfaces of a 3-level Hierarchic...
Pedro U. Lima, George N. Saridis
262
Voted
ABIALS
2008
Springer
15 years 6 months ago
Anticipatory Driving for a Robot-Car Based on Supervised Learning
Abstract. Prediction and Planning are essential elements of successful human driving, making them equally important for autonomously driving systems. Many approaches achieve planni...
Irene Markelic, Tomas Kulvicius, Minija Tamosiunai...