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GECCO
2003
Springer
133views Optimization» more  GECCO 2003»
15 years 9 months ago
Dynamic Strategies in a Real-Time Strategy Game
Abstract. Most modern real-time strategy computer games have a sophisticated but fixed ‘AI’ component that controls the computer’s actions. Once the user has learned how suc...
William Joseph Falke II, Peter Ross
NIPS
2008
15 years 5 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
ATAL
2010
Springer
15 years 5 months ago
Linear options
Learning, planning, and representing knowledge in large state t multiple levels of temporal abstraction are key, long-standing challenges for building flexible autonomous agents. ...
Jonathan Sorg, Satinder P. Singh
CORR
2010
Springer
152views Education» more  CORR 2010»
15 years 4 months ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná
AVI
2010
15 years 1 months ago
An infrastructure for creating graphical indicators of the learner profile by mashing up different sources
The procedures to collect information about users are well known in computer science till long time. They range from getting explicit information from users, required in order to ...
Luca Mazzola, Riccardo Mazza