Brief Biography
I am currently (August 2011 - May 2012) a visiting assistant professor at Ursinus College, but have elected to continue using Lehigh's web hosting until either they stop providing it or I find another institution that will be my home for more than one year.
Prior to coming to Ursinus (as an employee) I was a visiting instructor at Mansfield University of Pennsylvania (August 2010 - May 2011) and a doctoral student at Lehigh University (August 2004 - August 2011). For the first two of my years at Lehigh I was working with Prof. Hank Korth in multidatabase systems, while for the last five years I was working with Prof. Hector Munoz-Avila in the area of artificial intelligence. Before my association with Lehigh I was an undergraduate student at Ursinus College (August 2000 - May 2004).
I maintain a more personal (though equally infrequently-updated) web presence at http://chadhogg.name/~chad/.
Research
The topic of my dissertation research was learning knowledge artifacts for HTN planning (decomposition methods) from annotated tasks and plan traces. Source code, testing domains, and publications related to this work can be found at the HTN-Maker project webpage.
In addition to this primary topic, I had been involved in a number of other projects related to planning, case-based reasoning, reinforcement learning, and computer games as part of the Intelligent Decision Systems and Technologies (InSyTe) Lab at Lehigh. Currently I am interested in extending my dissertation work and pursuing other broad topics in artificial intelligence, including automated planning systems; classification, clustering, and other machine learning techniques; collaborative filtering systems, data mining, and web search; and heuristic music composition.
Courses
I used to distribute materials for courses that I was teaching through this website, but have removed them to save space. If you were a student in one of my earlier courses and would like a copy of the resources that we used in that course, please contact me directly.
- In spring 2012 I will be teaching CS 173: Introduction To Computer Science, CS 174: Data Structures, and CS 274: Computer Organization at Ursinus College.
- In fall 2011 I have been teaching CS 173: Introduction To Computer Science, CS 174: Data Structures, and CS 477: Artificial Intelligence at Ursinus College.
- In spring 2011, I taught CIS 1109: Explorations In Computer Science, CIS 3315: Data Structures, and CIS 3325: Operating Systems at Mansfield University of Pennsylvania.
- In fall 2010, I taught CIS 1115: Programming With Objects, CIS 3304: Advanced Web Design, and CIS 3311: Software Engineering at Mansfield University of Pennsylvania.
- In summer 2006, I taught CSE 271: Programming in C and the UNIX Environment at Lehigh University.
Publications
- Hogg, Chad; Lee-Urban, Stephen; Munoz-Avila, Hector; Auslander, Bryan; Smith, Megan. 2011. Game AI for Domination Games. In Artificial Intelligence for Computer Games, edited by Pedro A. Gonzalez Calero.
- Hogg, Chad; Kuter, Ugur; and Munoz-Avila, Hector. 2010. Learning Methods to Generate Good Plans: Integrating HTN Learning and Reinforcement Learning. In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10).
- Li, Hua; Munoz-Avila, Hector; Bramsen, Diane; Hogg, Chad; and Alonso, Rafael. 2009. Spatial Event Prediction by Combining Value Function Approximation and Case-Based Reasoning. In Proceedings of the 8th International Conference on Case-Based Reasoning (ICCBR-09).
- Hogg, Chad; Munoz-Avila, Hector; and Kuter, Ugur. 2009. Learning Hierarchical Task Networks for Nondeterministic Planning Domains. In Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence (IJCAI-09). [published version]
- Zhuo, Hankui; Yang, Qiang; Hu, Derek Hao; Hogg, Chad; and Munoz-Avila, Hector. 2009. Learning HTN Method Preconditions and Action Models from Partial Observations. In Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence (IJCAI-09).
- Hogg, Chad; Kuter, Ugur; and Munoz-Avila; Hector. 2009. From Plan Traces to Hierarchical Task Networks Using Reinforcements: A Preliminary Report. In Proceedings of the IJCAI-09 Workshop on Learning Structural Knowledge From Observations (StrucK-09).
- Zhuo, Hankui; Hu, Derek Hao; Yang, Qiang; Hogg, Chad; and Munoz-Avila; Hector. 2009. Learning Model Structures in AI Planning from Partial Observations. In Proceedings of the IJCAI-09 Workshop on Learning Structural Knowledge From Observations (StrucK-09).
- Hogg, Chad; Lee-Urban, Stephen; Auslander, Bryan; and Munoz-Avila, Hector. 2008. Discovering Feature Weights for Feature-Based Indexing of Q-Tables. In Proceedings of the Uncertainty and Knowledge Discovery in CBR Workshop at the 9th European Conference on Advances in Case-Based Reasoning (ECCBR-08).
- Auslander, Bryan; Lee-Urban, Stephen; Hogg, Chad; and Munoz-Avila, Hector. 2008. Recognizing The Enemy: Combining Reinforcement Learning with Strategy Selection using Case-Based Reasoning. In Proceedings of the 9th European Conference on Advances in Case-Based Reasoning (ECCBR-08).
- Hogg, Chad; Munoz-Avila, Hector; and Kuter, Ugur. 2008. HTN-MAKER: Learning HTNs with Minimal Additional Knowledge Engineering Required. In Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (AAAI-08).
- Hogg, Chad. 2007. From Task Definitions and Plan Traces to HTN Methods. In Proceedings of the Doctoral Consortium at the International Conference on Automated Planning and Scheduling (ICAPS-07).
- Hogg, Chad and Munoz-Avila, Hector. 2007. Learning Hierarchical Task Networks from Plan Traces. In Proceedings of the AI Planning and Learning Workshop (AIPL) at the International Conference on Automated Planning and Scheduling (ICAPS-07).
- Warfield, Ian; Hogg, Chad; Lee-Urban, Stephen; and Munoz-Avila, Hector. 2007. Adaptation of Hierarchical Task Network Plans. In Proceedings of the Twentieth Flairs International Conference (FLAIRS-07).
Resources
- My Curriculum Vitae.
- The presentation I gave at AAAI-10 for the paper "Learning Methods to Generate Good Plans: Integrating HTN Learning and Reinforcement Learning".
- The presentation I gave at IJCAI-09 for the paper "Learning Hierarchical Task Networks for Nondeterministic Planning Domains".
- The presentation I gave at AAAI-08 for the paper "HTN-Maker: Learning HTNs with Minimal Additional Knowledge Engineering Required".