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» A Failure to Learn from the Past
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AIIDE
2008
13 years 9 months ago
Combining Model-Based Meta-Reasoning and Reinforcement Learning for Adapting Game-Playing Agents
Human experience with interactive games will be enhanced if the software agents that play the game learn from their failures. Techniques such as reinforcement learning provide one...
Patrick Ulam, Joshua Jones, Ashok K. Goel
SIGOPS
2008
146views more  SIGOPS 2008»
13 years 7 months ago
Vigilant: out-of-band detection of failures in virtual machines
What do our computer systems do all day? How do we make sure they continue doing it when failures occur? Traditional approaches to answering these questions often involve inband m...
Dan Pelleg, Muli Ben-Yehuda, Richard Harper, Lisa ...
AIPS
2011
12 years 11 months ago
Planning and Acting in Incomplete Domains
Engineering complete planning domain descriptions is often very costly because of human error or lack of domain knowledge. Learning complete domain descriptions is also very chall...
Christopher Weber, Daniel Bryce
LAMAS
2005
Springer
14 years 26 days ago
The Success and Failure of Tag-Mediated Evolution of Cooperation
Use of tags to limit partner selection for playing has been shown to produce stable cooperation in agent populations playing the Prisoner’s Dilemma game. There is, however, a lac...
Austin McDonald, Sandip Sen
AGI
2008
13 years 8 months ago
Seven Principles of Synthetic Intelligence
Understanding why the original project of Artificial Intelligence is widely regarded as a failure and has been abandoned even by most of contemporary AI research itself may prove c...
Joscha Bach