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» Learning complex problem solving expertise from failures
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ICML
2004
IEEE
14 years 8 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
AAAI
2004
13 years 9 months ago
Towards Autonomic Computing: Adaptive Job Routing and Scheduling
Computer systems are rapidly becoming so complex that maintaining them with human support staffs will be prohibitively expensive and inefficient. In response, visionaries have beg...
Shimon Whiteson, Peter Stone
NIPS
1993
13 years 9 months ago
Robust Reinforcement Learning in Motion Planning
While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
Satinder P. Singh, Andrew G. Barto, Roderic A. Gru...
AAMAS
2004
Springer
13 years 7 months ago
Autonomous Agents that Learn to Better Coordinate
A fundamental difficulty faced by groups of agents that work together is how to efficiently coordinate their efforts. This coordination problem is both ubiquitous and challenging,...
Andrew Garland, Richard Alterman
ICSE
2009
IEEE-ACM
14 years 4 days ago
License integration patterns: Addressing license mismatches in component-based development
In this paper we address the problem of combining software components with different and possibly incompatible legal licenses to create a software application that does not viola...
Daniel M. Germán, Ahmed E. Hassan