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FLAIRS
2003
15 years 7 months ago
Learning from Reinforcement and Advice Using Composite Reward Functions
1 Reinforcement learning has become a widely used methodology for creating intelligent agents in a wide range of applications. However, its performance deteriorates in tasks with s...
Vinay N. Papudesi, Manfred Huber
DALT
2007
Springer
16 years 14 days ago
Composing High-Level Plans for Declarative Agent Programming
Abstract. Research on practical models of autonomous agents has largely focused on a procedural view of goal achievement. This allows for efficient implementations, but prevents an...
Felipe Rech Meneguzzi, Michael Luck
AAMAS
2007
Springer
15 years 6 months ago
Parallel Reinforcement Learning with Linear Function Approximation
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
Matthew Grounds, Daniel Kudenko
ATAL
2008
Springer
15 years 8 months ago
Autonomic machine control: a case study
This paper describes an autonomic machine control system applied to the adaptive control of a modular soldering machine. The particular case concerns the creation of a novel modul...
Christian Dannegger, Dominic A. P. Greenwood
AAAI
2010
15 years 7 months ago
Recognizing Multi-Agent Activities from GPS Data
Recent research has shown that surprisingly rich models of human behavior can be learned from GPS (positional) data. However, most research to date has concentrated on modeling si...
Adam Sadilek, Henry A. Kautz