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Travelled to:
1 × Australia
1 × Finland
1 × Germany
1 × Slovenia
1 × United Kingdom
11 × USA
Collaborated with:
M.T.Gervasio J.Gratch A.Laud A.Epshteyn S.A.Chien Q.Sun M.Brodie S.Bennett S.A.Rajamoney A.Vogel R.C.Schank J.L.Kolodner K.Yotov X.Li G.Ren M.Cibulskis M.J.Garzarán D.A.Padua K.Pingali P.Stodghill P.Wu
Talks about:
learn (12) reinforc (5) explan (5) approach (4) plan (4) control (3) knowledg (2) retriev (2) reactiv (2) problem (2)

Person: Gerald DeJong

DBLP DBLP: DeJong:Gerald

Contributed to:

ICML 20082008
ICML 20062006
ICML 20052005
ICML 20032003
PLDI 20032003
ICML 20022002
ICML 20002000
ICML 19991999
ICML 19951995
ICML 19941994
ICML 19931993
ML 19921992
ML 19911991
ML 19891989
ML 19881988
SIGIR 19831983
SIGIR 19801980

Wrote 19 papers:

ICML-2008-EpshteynVD #learning
Active reinforcement learning (AE, AV, GD), pp. 296–303.
ICML-2006-EpshteynD #learning
Qualitative reinforcement learning (AE, GD), pp. 305–312.
ICML-2005-SunD #approach #learning
Explanation-Augmented SVM: an approach to incorporating domain knowledge into SVM learning (QS, GD), pp. 864–871.
ICML-2003-LaudD #analysis #learning
The Influence of Reward on the Speed of Reinforcement Learning: An Analysis of Shaping (AL, GD), pp. 440–447.
PLDI-2003-YotovLRCDGPPSW #comparison #empirical #modelling #optimisation
A comparison of empirical and model-driven optimization (KY, XL, GR, MC, GD, MJG, DAP, KP, PS, PW), pp. 63–76.
ICML-2002-LaudD #behaviour #learning
Reinforcement Learning and Shaping: Encouraging Intended Behaviors (AL, GD), pp. 355–362.
ICML-2000-DeJong #empirical #learning
Hidden Strengths and Limitations: An Empirical Investigation of Reinforcement Learning (GD), pp. 215–222.
ICML-1999-BrodieD #induction #learning #using
Learning to Ride a Bicycle using Iterated Phantom Induction (MB, GD), pp. 57–66.
ICML-1995-DeJong #case study
A Case Study of Explanation-Based Control (GD), pp. 167–175.
ICML-1994-GervasioD #approach #incremental #learning
An Incremental Learning Approach for Completable Planning (MTG, GD), pp. 78–86.
ICML-1993-GratchCD #learning #network #scheduling
Learning Search Control Knowledge for Deep Space Network Scheduling (JG, SAC, GD), pp. 135–142.
ML-1992-GratchD #analysis #learning #problem
An Analysis of Learning to Plan as a Search Problem (JG, GD), pp. 179–188.
ML-1991-BennettD #probability
Comparing Stochastic Planning to the Acquisition of Increasingly Permissive Plans (SB, GD), pp. 586–590.
ML-1991-ChienGD #learning #on the
On Becoming Decreasingly Reactive: Learning to Deliberate Minimally (SAC, MTG, GD), pp. 288–292.
ML-1991-GratchD #approach #effectiveness #hybrid
A Hybrid Approach to Guaranteed Effective Control Strategies (JG, GD), pp. 509–513.
ML-1989-GervasioD #learning
Explanation-Based Learning of Reactive Operations (MTG, GD), pp. 252–254.
ML-1988-RajamoneyD #approach #multi #problem #reduction
Active Explanation Reduction: An Approach to the Multiple Explanations Problem (SAR, GD), pp. 242–255.
SIGIR-1983-DeJong #information retrieval
Artificial Intelligence Implications for Information Retrieval (GD), pp. 10–17.
SIGIR-1980-SchankKD #concept #information retrieval
Conceptual Information Retrieval (RCS, JLK, GD), pp. 94–116.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.