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» Problems of learning in multi-agent systems
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CCIA
2006
Springer
14 years 2 months ago
Learning from cooperation using justifications
In multi-agent systems, individual problem solving capabilities can be improved thanks to the interaction with other agents. In the classification problem solving task each agent i...
Eloi Puertas, Eva Armengol
IJCAI
1989
14 years 9 days ago
Selective Learning of Macro-operators with Perfect Causality
A macro-operator is an integrated operator consisting of plural primitive operators and enables a problem solver to solve more efficiently. However, if a learning system generates...
Seiji Yamada, Sabinro Tsuji
HIS
2004
14 years 17 days ago
A Case-Based Recommender for Task Assignment in Heterogeneous Computing Systems
Case-based reasoning (CBR) is a knowledge-based problem-solving technique, which is based on reuse of previous experiences. In this paper we propose a new model for static task as...
S. Ghanbari, Mohammad Reza Meybodi, Kambiz Badie
MSE
2005
IEEE
133views Hardware» more  MSE 2005»
14 years 4 months ago
Embedded System Design with FPGAs Using HDLs (Lessons Learned and Pitfalls to Be Avoided)
This paper describes the authors experience with teaching VHDL (and more recently, Verilog) to undergraduate and graduate students at WPI and to engineers through various short co...
R. James Duckworth
AAAI
2010
14 years 18 days ago
An Integrated Systems Approach to Explanation-Based Conceptual Change
Understanding conceptual change is an important problem in modeling human cognition and in making integrated AI systems that can learn autonomously. This paper describes a model o...
Scott Friedman, Kenneth D. Forbus