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133
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ICML
1999
IEEE
15 years 8 months ago
Learning Hierarchical Performance Knowledge by Observation
Developing automated agents that intelligently perform complex real world tasks is time consuming and expensive. The most expensive part of developing these intelligent task perfo...
Michael van Lent, John E. Laird
STOC
2010
ACM
269views Algorithms» more  STOC 2010»
15 years 8 months ago
Approximations for the Isoperimetric and Spectral Profile of Graphs and Related Parameters
The spectral profile of a graph is a natural generalization of the classical notion of its Rayleigh quotient. Roughly speaking, given a graph G, for each 0 < < 1, the spect...
Prasad Raghavendra, David Steurer and Prasad Tetal...
121
Voted
ICCBR
2010
Springer
15 years 8 months ago
Imitating Inscrutable Enemies: Learning from Stochastic Policy Observation, Retrieval and Reuse
In this paper we study the topic of CBR systems learning from observations in which those observations can be represented as stochastic policies. We describe a general framework wh...
Kellen Gillespie, Justin Karneeb, Stephen Lee-Urba...
ATAL
2006
Springer
15 years 7 months ago
Robust recognition of physical team behaviors using spatio-temporal models
This paper presents a framework for robustly recognizing physical team behaviors by exploiting spatio-temporal patterns. Agent team behaviors in athletic and military domains typi...
Gita Sukthankar, Katia P. Sycara
HT
2009
ACM
15 years 7 months ago
Four measures for the dynamics of coalitions in social networks
We introduce four measures for the change of coalitions in social networks. The first one measures the change of the agents in the network over time, The second one measures the ...
Guido Boella, Leendert van der Torre, Serena Villa...