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NIPS
1993
14 years 11 months ago
Convergence of Stochastic Iterative Dynamic Programming Algorithms
Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms,includ...
Tommi Jaakkola, Michael I. Jordan, Satinder P. Sin...
ICML
2010
IEEE
14 years 11 months ago
Inverse Optimal Control with Linearly-Solvable MDPs
We present new algorithms for inverse optimal control (or inverse reinforcement learning, IRL) within the framework of linearlysolvable MDPs (LMDPs). Unlike most prior IRL algorit...
Dvijotham Krishnamurthy, Emanuel Todorov
PEPM
2011
ACM
14 years 19 days ago
Adaptation-based programming in java
Writing deterministic programs is often difficult for problems whose optimal solutions depend on unpredictable properties of the programs’ inputs. Difficulty is also encounter...
Tim Bauer, Martin Erwig, Alan Fern, Jervis Pinto
IUI
2006
ACM
15 years 3 months ago
Are two talking heads better than one?: when should use more than one agent in e-learning?
Recent interest in the use of software character agents raises the issue of how many agents should be used in online learning. In this paper we review evidence concerning the rela...
Hua Wang, Mark H. Chignell, Mitsuru Ishizuka
GECCO
2008
Springer
121views Optimization» more  GECCO 2008»
14 years 11 months ago
Fast rule representation for continuous attributes in genetics-based machine learning
Genetic-Based Machine Learning Systems (GBML) are comparable in accuracy with other learning methods. However, efficiency is a significant drawback. This paper presents a new rep...
Jaume Bacardit, Natalio Krasnogor