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ICMAS
1998
15 years 2 months ago
Multi-Machine Scheduling - A Multi-Agent Learning Approach
Multi-machine scheduling, that is, the assigment of jobs to machines such that certain performance demands like cost and time effectiveness are fulfilled, is a ubiquitous and comp...
Wilfried Brauer, Gerhard Weiß
80
Voted
MICAI
2000
Springer
15 years 4 months ago
Memory Based Reasoning and Agents Adaptive Behavior
The main purpose of this work is to explore the application of Memory Based Reasoning (MBR) to adaptive behavior in agents. We discuss the design of an interface agent for e-mail m...
Ana S. Aguera, Alejandro Guerra, Manuel Mart&iacut...
123
Voted
CEC
2005
IEEE
15 years 2 months ago
Evolution and prioritization of survival strategies for a simulated robot in Xpilot
Simulated evolution by the use of Genetic Algorithms (GA) is presented as the solution to a twofaceted problem: the challenge for an autonomous agent to learn the reactive componen...
Gary B. Parker, Timothy S. Doherty, Matt Parker
ICTAI
2006
IEEE
15 years 6 months ago
Intelligent Optimization via Learnable Evolution Model
A new method for optimizing complex functions and systems is described that employs Learnable Evolution Model (LEM), a form of non-Darwinian evolutionary computation guided by mac...
Ryszard S. Michalski, Janusz Wojtusiak, Kenneth A....
95
Voted
AIED
2007
Springer
15 years 6 months ago
Tools for Authoring a Dialogue Agent that Participates in Learning Studies
TuTalk supports the rapid development of dialogue agents for learning applications. It enables an experimenter to create a dialogue agent with either minimal or no programming and ...
Pamela W. Jordan, Brian Hall, Michael A. Ringenber...