Explanation-Based Learning of Reactive Operations. - Melinda T. Gervasio; Gerald DeJong (ML, 1989)

Learning General Completable Reactive Plans. - Melinda T. Gervasio (AAAI, 1990)

On Becoming Decreasingly Reactive: Learning to Deliberate Minimally. - Steve A. Chien; Melinda T. Gervasio; Gerald DeJong (ML, 1991)

Explanation-based learning for intelligent process planning. - Sang-Chan Park; Melinda T. Gervasio; Michael J. Shaw; Gerald DeJong (IEEE Trans. Syst. Man Cybern., 1993)

An Incremental Learning Approach for Completable Planning. - Melinda T. Gervasio; Gerald DeJong (ICML, 1994)

Learning to Predict User Operations for Adaptive Scheduling. - Melinda T. Gervasio; Wayne Iba; Pat Langley (AAAI/IAAI, 1998)

Learning User Evaluation Functions for Adaptive Scheduling Assistance. - Melinda T. Gervasio; Wayne Iba; Pat Langley (ICML, 1999)

Adapting to User Preferences in Crisis Response. - Wayne Iba; Melinda T. Gervasio (IUI, 1999)

An adaptive stock tracker for personalized trading advice. - Jungsoon P. Yoo; Melinda T. Gervasio; Pat Langley (IUI, 2003)

Personalized trading recommendation system. - Jungsoon P. Yoo; Melinda T. Gervasio; Pat Langley (IUI, 2003)

A Personalized Time Management Assistant: Research Directions. - Pauline M. Berry; Melinda T. Gervasio; Tomás E. Uribe; Martha E. Pollack; Michael D. Moffitt (AAAI Spring Symposium: Persistent Assistants: Living and Working with AI, 2005)

Active preference learning for personalized calendar scheduling assistance. - Melinda T. Gervasio; Michael D. Moffitt; Martha E. Pollack; Joseph M. Taylor; Tomás E. Uribe (IUI, 2005)

Multi-Criteria Evaluation in User-Centric Distributed Scheduling Agents. - Pauline M. Berry; Melinda T. Gervasio; Bart Peintner; Tomás E. Uribe; Neil Yorke-Smith (AAAI Spring Symposium: Distributed Plan and Schedule Management, 2006)

Deploying a personalized time management agent. - Pauline Berry; Bart Peintner; Ken Conley; Melinda T. Gervasio; Tomás E. Uribe; Neil Yorke-Smith (AAMAS, 2006)

An Intelligent Personal Assistant for Task and Time Management. - Karen L. Myers; Pauline Berry; Jim Blythe; Ken Conley; Melinda T. Gervasio; Deborah L. McGuinness; David N. Morley; Avi Pfeffer; Martha E. Pollack; Milind Tambe (AI Mag., 2007)

Iteration Learning by Demonstration. - Steven Eker; Thomas J. Lee; Melinda T. Gervasio (AAAI Spring Symposium: Agents that Learn from Human Teachers, 2009)

Question Asking to Inform Preference Learning: A Case Study. - Melinda T. Gervasio; Karen L. Myers; Marie desJardins; Fusun Yaman (AAAI Spring Symposium: Agents that Learn from Human Teachers, 2009)

Evaluating User-Adaptive Systems: Lessons from Experiences with a Personalized Meeting Scheduling Assistant. - Pauline M. Berry; Thierry Donneau-Golencer; Khang Duong; Melinda T. Gervasio; Bart Peintner; Neil Yorke-Smith (IAAI, 2009)

Learning by Demonstration to Support Military Planning and Decision Making. - Thomas D. Garvey; Melinda T. Gervasio; Thomas J. Lee; Karen L. Myers; Carl Angiolillo; Matthew E. Gaston; Janette Knittel; Jake Kolojejchick (IAAI, 2009)

What were you thinking?: filling in missing dataflow through inference in learning from demonstration. - Melinda T. Gervasio; Janet L. Murdock (IUI, 2009)

From geek to sleek: integrating task learning tools to support end users in real-world applications. - Aaron Spaulding; Jim Blythe; Will Haines; Melinda T. Gervasio (IUI, 2009)

Goal-Directed Metacontrol for Integrated Procedure Learning. - Jihie Kim; Karen L. Myers; Melinda T. Gervasio; Yolanda Gil (Metareasoning, 2011)

Learning by Demonstration Technology for Military Planning and Decision Making: A Deployment Story. - Karen L. Myers; Jake Kolojejchick; Carl Angiolillo; Tim Cummings; Tom Garvey; Melinda T. Gervasio; Will Haines; Chris Jones 002; Janette Knittel; David N. Morley; William Ommert; Scott Potter (IAAI, 2011)

How to serve soup: interleaving demonstration and assisted editing to support nonprogrammers. - Melinda T. Gervasio; Will Haines; David N. Morley; Thomas J. Lee; C. Adam Overholtzer; Shahin Saadati; Aaron Spaulding (IUI, 2011)

Learning to ask the right questions to help a learner learn. - Melinda T. Gervasio; Eric Yeh; Karen L. Myers (IUI, 2011)

PTIME: Personalized assistance for calendaring. - Pauline M. Berry; Melinda T. Gervasio; Bart Peintner; Neil Yorke-Smith (ACM Trans. Intell. Syst. Technol., 2011)

Learning by Demonstration for a Collaborative Planning Environment. - Karen L. Myers; Jake Kolojejchick; Carl Angiolillo; Tim Cummings; Tom Garvey; Matthew E. Gaston; Melinda T. Gervasio; Will Haines; Chris Jones 002; Kellie Keifer; Janette Knittel; David N. Morley; et al. (AI Mag., 2012)

Drill Evaluation for Training Procedural Skills. - Karen L. Myers; Melinda T. Gervasio; Christian Jones; Kyle McIntyre; Kellie Keifer (AIED, 2013)

Discovering action idioms bridging the gap between system-level events and human-level actions. - Melinda T. Gervasio; Thomas J. Lee (VL/HCC, 2013)

Solution Authoring via Demonstration and Annotation: An Empirical Study. - Karen L. Myers; Melinda T. Gervasio (ICALT, 2016)

Evaluating intelligent knowledge systems: experiences with a user-adaptive assistant agent. - Pauline M. Berry; Thierry Donneau-Golencer; Khang Duong; Melinda T. Gervasio; Bart Peintner; Neil Yorke-Smith (Knowl. Inf. Syst., 2017)

Explanation to Avert Surprise. - Melinda T. Gervasio; Karen L. Myers; Eric Yeh; Boone Adkins (IUI Workshops, 2018)

Interestingness Elements for Explainable Reinforcement Learning through Introspection. - Pedro Sequeira; Eric Yeh; Melinda T. Gervasio (IUI Workshops, 2019)

Interestingness elements for explainable reinforcement learning: Understanding agents' capabilities and limitations. - Pedro Sequeira; Melinda T. Gervasio (Artif. Intell., 2020)

Confidence Calibration for Domain Generalization under Covariate Shift. - Yunye Gong; Xiao Lin; Yi Yao; Thomas G. Dietterich; Ajay Divakaran; Melinda T. Gervasio (ICCV, 2021)

Outcome-Guided Counterfactuals for Reinforcement Learning Agents from a Jointly Trained Generative Latent Space. - Eric Yeh; Pedro Sequeira; Jesse Hostetler; Melinda T. Gervasio (CoRR, 2022)

A Framework for Understanding and Visualizing Strategies of RL Agents. - Pedro Sequeira; Daniel Elenius; Jesse Hostetler; Melinda T. Gervasio (CoRR, 2022)

Global and Local Analysis of Interestingness for Competency-Aware Deep Reinforcement Learning. - Pedro Sequeira; Jesse Hostetler; Melinda T. Gervasio (CoRR, 2022)

IxDRL: A Novel Explainable Deep Reinforcement Learning Toolkit Based on Analyses of Interestingness. - Pedro Sequeira; Melinda T. Gervasio (xAI (1), 2023)

Outcome-Guided Counterfactuals from a Jointly Trained Generative Latent Space. - Eric Yeh; Pedro Sequeira; Jesse Hostetler; Melinda T. Gervasio (xAI (3), 2023)

Confidence Calibration for Systems with Cascaded Predictive Modules. - Yunye Gong; Yi Yao; Xiao Lin; Ajay Divakaran; Melinda T. Gervasio (CoRR, 2023)

AI as Collaborative Partner: Rethinking Human-AI Teaming for the Real World. - Melinda T. Gervasio; Pedro Sequeira; Eric Yeh; Nicholas Marion; Sarah Bakst; Helen Gent (AAAI Spring Symposia, 2025)

ToMCAT: Theory-of-Mind for Cooperative Agents in Teams via Multiagent Diffusion Policies. - Pedro Sequeira; Vidyasagar Sadhu; Melinda T. Gervasio (CoRR, 2025)