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IROS
2006
IEEE
107views Robotics» more  IROS 2006»
14 years 4 months ago
Heterogeneous and Hierarchical Cooperative Learning via Combining Decision Trees
Abstract— Decision trees, being human readable and hierarchically structured, provide a suitable mean to derive state-space abstraction and simplify the inclusion of the availabl...
Masoud Asadpour, Majid Nili Ahmadabadi, Roland Sie...
AIPS
2008
14 years 18 days ago
Learning Heuristic Functions through Approximate Linear Programming
Planning problems are often formulated as heuristic search. The choice of the heuristic function plays a significant role in the performance of planning systems, but a good heuris...
Marek Petrik, Shlomo Zilberstein
AAAI
2010
13 years 11 months ago
Multi-Agent Learning with Policy Prediction
Due to the non-stationary environment, learning in multi-agent systems is a challenging problem. This paper first introduces a new gradient-based learning algorithm, augmenting th...
Chongjie Zhang, Victor R. Lesser
ICGA
2008
100views Optimization» more  ICGA 2008»
13 years 10 months ago
Learning the Piece Values for Three Chess Variants
A set of experiments for learning the values of chess pieces is described for the popular chess variants Crazyhouse Chess, Suicide Chess, and Atomic Chess. We follow an establishe...
Sacha Droste, Johannes Fürnkranz
ACL
2010
13 years 8 months ago
Reading between the Lines: Learning to Map High-Level Instructions to Commands
In this paper, we address the task of mapping high-level instructions to sequences of commands in an external environment. Processing these instructions is challenging--they posit...
S. R. K. Branavan, Luke S. Zettlemoyer, Regina Bar...