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» Using model knowledge for learning inverse dynamics
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114
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BMCBI
2007
115views more  BMCBI 2007»
15 years 3 months ago
Comparing sequences without using alignments: application to HIV/SIV subtyping
Background: In general, the construction of trees is based on sequence alignments. This procedure, however, leads to loss of informationwhen parts of sequence alignments (for inst...
Gilles Didier, Laurent Debomy, Maude Pupin, Ming Z...
109
Voted
AAAI
2008
15 years 6 months ago
Potential-based Shaping in Model-based Reinforcement Learning
Potential-based shaping was designed as a way of introducing background knowledge into model-free reinforcement-learning algorithms. By identifying states that are likely to have ...
John Asmuth, Michael L. Littman, Robert Zinkov
165
Voted
COOPIS
2002
IEEE
15 years 8 months ago
Discovering Emergent Virtual Work Processes in Collaborative Systems
The design of virtual workplaces that can support virtual work processes has traditionally been either ad-hoc, or has been influenced by the top-down approaches, such as ‘virtua...
Simeon J. Simoff, Robert P. Biuk-Aghai
107
Voted
ISTA
2007
15 years 5 months ago
Game Theory-based Data Mining Technique for Strategy Making of a Soccer Simulation Coach Agent
: Soccer simulation is an effort to motivate researchers to perform artificial and robotic intelligence investigations in a multi-agent system framework. In this paper, we propose ...
Amin Milani Fard, Vahid Salmani, Mahmoud Naghibzad...
124
Voted
GECCO
2007
Springer
178views Optimization» more  GECCO 2007»
15 years 9 months ago
Coevolution of intelligent agents using cartesian genetic programming
A coevolutionary competitive learning environment for two antagonistic agents is presented. The agents are controlled by a new kind of computational network based on a compartment...
Gul Muhammad Khan, Julian Francis Miller, David M....