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DAGSTUHL
2003
13 years 11 months ago
Maximizing Learning Progress: An Internal Reward System for Development
This chapter presents a generic internal reward system that drives an agent to increase the complexity of its behavior. This reward system does not reinforce a predefined task. It...
Frédéric Kaplan, Pierre-Yves Oudeyer
ANTSW
2008
Springer
13 years 11 months ago
A Simulation Study of Routing Performance in Realistic Urban Scenarios for MANETs
Abstract. We study through simulation the performance of two MANET routing algorithms in a realistic urban environment. The two algorithms, AODV and AntHocNet, are representative o...
Gianni Di Caro, Frederick Ducatelle, Luca Maria Ga...
KI
2008
Springer
13 years 9 months ago
Autonomous Learning of User's Preferences Improved through User Feedback
Ambient Intelligent (AmI) environments are supposed to act proactively anticipating the user's needs and preferences, therefore the capability of an AmI system to learn those ...
Asier Aztiria, Juan Carlos Augusto, Alberto Izagui...
ATAL
2007
Springer
14 years 3 months ago
Real-time agent characterization and prediction
Reasoning about agents that we observe in the world is challenging. Our available information is often limited to observations of the agent’s external behavior in the past and p...
H. Van Dyke Parunak, Sven Brueckner, Robert S. Mat...
AGENTS
1997
Springer
14 years 1 months ago
Increasing Believability in Animated Pedagogical Agents
Animated pedagogical agents o er great promise for knowledge-based learning environments. In addition to coupling feedback capabilities with a strong visual presence, these agents...
James C. Lester, Brian A. Stone