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» Learning behavior styles with inverse reinforcement learning
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PKDD
2010
Springer
158views Data Mining» more  PKDD 2010»
13 years 6 months ago
Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
Katya Scheinberg, Irina Rish
ROBOCUP
2004
Springer
147views Robotics» more  ROBOCUP 2004»
14 years 1 months ago
Learning to Drive and Simulate Autonomous Mobile Robots
We show how to apply learning methods to two robotics problems, namely the optimization of the on-board controller of an omnidirectional robot, and the derivation of a model of the...
Alexander Gloye, Cüneyt Göktekin, Anna E...
GECCO
2008
Springer
148views Optimization» more  GECCO 2008»
13 years 8 months ago
On the effects of node duplication and connection-oriented constructivism in neural XCSF
For artificial entities to achieve high degrees of autonomy they will need to display appropriate adaptability. In this sense adaptability includes representational flexibility gu...
Gerard David Howard, Larry Bull
GAMEON
2003
13 years 9 months ago
Automatic Acquisition of Actions for Animated Agents
The generation of animated human figures especially in crowd scenes has many applications in such domains as the special effects industry, computer games or for the simulation of ...
Adam Szarowicz, Marek Mittmann, Paolo Remagnino, J...
AAMAS
2005
Springer
13 years 7 months ago
Cooperative Multi-Agent Learning: The State of the Art
Cooperative multi-agent systems are ones in which several agents attempt, through their interaction, to jointly solve tasks or to maximize utility. Due to the interactions among t...
Liviu Panait, Sean Luke