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ICRA
2006
IEEE
104views Robotics» more  ICRA 2006»
15 years 3 months ago
Implicit Coordination in Robotic Teams using Learned Prediction Models
— Many application tasks require the cooperation of two or more robots. Humans are good at cooperation in shared workspaces, because they anticipate and adapt to the intentions a...
Freek Stulp, Michael Isik, Michael Beetz
CORR
2007
Springer
73views Education» more  CORR 2007»
14 years 9 months ago
Universal Reinforcement Learning
—We consider an agent interacting with an unmodeled environment. At each time, the agent makes an observation, takes an action, and incurs a cost. Its actions can influence futu...
Vivek F. Farias, Ciamac Cyrus Moallemi, Tsachy Wei...
69
Voted
ATAL
2008
Springer
14 years 11 months ago
Automated design of scoring rules by learning from examples
Scoring rules are a broad and concisely-representable class of voting rules which includes, for example, Plurality and Borda. Our main result asserts that the class of scoring rul...
Ariel D. Procaccia, Aviv Zohar, Jeffrey S. Rosensc...
NIPS
1996
14 years 11 months ago
Reinforcement Learning for Mixed Open-loop and Closed-loop Control
Closed-loop control relies on sensory feedback that is usually assumed to be free. But if sensing incurs a cost, it may be coste ective to take sequences of actions in open-loop m...
Eric A. Hansen, Andrew G. Barto, Shlomo Zilberstei...
AGENTS
1999
Springer
15 years 2 months ago
Team-Partitioned, Opaque-Transition Reinforcement Learning
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Peter Stone, Manuela M. Veloso