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ECML
2007
Springer
15 years 7 months ago
Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
Gerhard Neumann, Michael Pfeiffer, Wolfgang Maass
AAAI
2007
15 years 5 months ago
RETALIATE: Learning Winning Policies in First-Person Shooter Games
In this paper we present RETALIATE, an online reinforcement learning algorithm for developing winning policies in team firstperson shooter games. RETALIATE has three crucial chara...
Megan Smith, Stephen Lee-Urban, Hector Muño...
110
Voted
COLT
2008
Springer
15 years 5 months ago
Learning Rotations
An algorithm is presented for online learning of rotations. The proposed algorithm involves matrix exponentiated gradient updates and is motivated by the von Neumann divergence. T...
Adam M. Smith, Manfred K. Warmuth
115
Voted
EDM
2010
185views Data Mining» more  EDM 2010»
15 years 5 months ago
Analysis of Productive Learning Behaviors in a Structured Inquiry Cycle Using Hidden Markov Models
This paper demonstrates the generality of the hidden Markov model approach for exploratory sequence analysis by applying the methodology to study students' learning behaviors ...
Hogyeong Jeong, Gautam Biswas, Julie Johnson, Larr...
123
Voted
NIPS
2007
15 years 5 months ago
Learning to classify complex patterns using a VLSI network of spiking neurons
We propose a compact, low power VLSI network of spiking neurons which can learn to classify complex patterns of mean firing rates on–line and in real–time. The network of int...
Srinjoy Mitra, Giacomo Indiveri, Stefano Fusi