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2020 – today
- 2024
[c10]Chad Hogg
:
A Case For Reflection In Autograding. ITiCSE (1) 2024- 2022
- [c9]Chad Hogg, Maria Jump:
Designing Autograders for Novice Programmers. SIGCSE (2) 2022: 1200
2010 – 2019
- 2016
- [j1]Chad Hogg, Héctor Muñoz-Avila, Ugur Kuter:
Learning Hierarchical Task Models from Input Traces. Comput. Intell. 32(1): 3-48 (2016) - 2010
- [c8]Chad Hogg, Ugur Kuter, Hector Muñoz-Avila:
Learning Methods to Generate Good Plans: Integrating HTN Learning and Reinforcement Learning. AAAI 2010: 1530-1535
2000 – 2009
- 2009
- [c7]Hua Li, Héctor Muñoz-Avila, Diane Bramsen, Chad Hogg, Rafael Alonso:
Spatial Event Prediction by Combining Value Function Approximation and Case-Based Reasoning. ICCBR 2009: 465-478 - [c6]Chad Hogg, Ugur Kuter, Héctor Muñoz-Avila:
Learning Hierarchical Task Networks for Nondeterministic Planning Domains. IJCAI 2009: 1708-1714 - [c5]Hankz Hankui Zhuo, Derek Hao Hu, Chad Hogg, Qiang Yang, Hector Muñoz-Avila:
Learning HTN Method Preconditions and Action Models from Partial Observations. IJCAI 2009: 1804-1810 - 2008
- [c4]Chad Hogg, Héctor Muñoz-Avila, Ugur Kuter:
HTN-MAKER: Learning HTNs with Minimal Additional Knowledge Engineering Required. AAAI 2008: 950-956 - [c3]Bryan Auslander, Stephen Lee-Urban, Chad Hogg, Héctor Muñoz-Avila:
Recognizing the Enemy: Combining Reinforcement Learning with Strategy Selection Using Case-Based Reasoning. ECCBR 2008: 59-73 - [c2]Chad Hogg, Stephen Lee-Urban, Bryan Auslander, Héctor Muñoz-Avila:
Discovering Feature Weights for Feature-based Indexing of Q-tables. ECCBR Workshops 2008: 131-142 - 2007
- [c1]Ian Warfield, Chad Hogg, Stephen Lee-Urban, Hector Muñoz-Avila:
Adaptation of Hierarchical Task Network Plans. FLAIRS 2007: 429-434
Coauthor Index
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