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ORCIDSheila A. McIlraith
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- affiliation: University of Toronto, Canada
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2020 – today
- 2023
[j31]Rodrigo Toro Icarte
, Toryn Q. Klassen, Richard Valenzano, Margarita P. Castro, Ethan Waldie, Sheila A. McIlraith:
Learning reward machines: A study in partially observable reinforcement learning. Artif. Intell. 323: 103989 (2023)- [j30]Pouya Shati, Eldan Cohen, Sheila A. McIlraith:
SAT-based optimal classification trees for non-binary data. Constraints An Int. J. 28(2): 166-202 (2023) - [c137]Toryn Q. Klassen, Parand Alizadeh Alamdari, Sheila A. McIlraith:
Epistemic Side Effects: An AI Safety Problem. AAMAS 2023: 1797-1801 - [c136]Pouya Shati, Eldan Cohen, Sheila A. McIlraith:
SAT-Based Learning of Compact Binary Decision Diagrams for Classification. CP 2023: 33:1-33:19 - [c135]Andrew Wang, Andrew C. Li, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith:
Learning Belief Representations for Partially Observable Deep RL. ICML 2023: 35970-35988 - [c134]Pouya Shati, Eldan Cohen, Sheila A. McIlraith:
Optimal Decision Trees For Interpretable Clustering with Constraints. IJCAI 2023: 2022-2030 - [c133]Toryn Q. Klassen, Christian Muise, Sheila A. McIlraith:
Planning with Epistemic Preferences. KR 2023: 752-756 - [c132]Diane Horton, David Liu, Sheila A. McIlraith, Nina Wang:
Is More Better When Embedding Ethics in CS Courses? SIGCSE (1) 2023: 652-658 - [i27]Phillip J. K. Christoffersen, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith:
Learning Symbolic Representations for Reinforcement Learning of Non-Markovian Behavior. CoRR abs/2301.02952 (2023) - [i26]Pouya Shati, Eldan Cohen, Sheila A. McIlraith:
Optimal Decision Trees For Interpretable Clustering with Constraints. CoRR abs/2301.12671 (2023) - [i25]Shalev Lifshitz, Keiran Paster, Harris Chan, Jimmy Ba, Sheila A. McIlraith:
STEVE-1: A Generative Model for Text-to-Behavior in Minecraft. CoRR abs/2306.00937 (2023) - [i24]Yoshua Bengio, Geoffrey E. Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, Gillian K. Hadfield, Jeff Clune, Tegan Maharaj, Frank Hutter, Atilim Günes Baydin, Sheila A. McIlraith, Qiqi Gao, Ashwin Acharya, David Krueger, Anca D. Dragan, Philip H. S. Torr, Stuart Russell, Daniel Kahneman, Jan Brauner, Sören Mindermann:
Managing AI Risks in an Era of Rapid Progress. CoRR abs/2310.17688 (2023) - 2022
- [j29]Christian Muise, Vaishak Belle, Paolo Felli, Sheila A. McIlraith, Tim Miller, Adrian R. Pearce, Liz Sonenberg:
Efficient multi-agent epistemic planning: Teaching planners about nested belief. Artif. Intell. 302: 103605 (2022) - [j28]Jorge A. Baier, Sheila A. McIlraith:
Knowledge-based programs as building blocks for planning. Artif. Intell. 303: 103634 (2022) - [j27]Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith:
Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning. J. Artif. Intell. Res. 73: 173-208 (2022) - [c131]Toryn Q. Klassen, Sheila A. McIlraith, Christian Muise, Jarvis Xu:
Planning to Avoid Side Effects. AAAI 2022: 9830-9839 - [c130]Maayan Shvo, Toryn Q. Klassen, Sheila A. McIlraith:
Resolving Misconceptions about the Plans of Agents via Theory of Mind. ICAPS 2022: 719-729 - [c129]Parand Alizadeh Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith:
Be Considerate: Avoiding Negative Side Effects in Reinforcement Learning. AAMAS 2022: 18-26 - [c128]Maayan Shvo, Ruthrash Hari, Ziggy O'Reilly, Sophia Abolore, Sze-Yuh Nina Wang, Sheila A. McIlraith:
Proactive Robotic Assistance via Theory of Mind. IROS 2022: 9148-9155 - [c127]Keiran Paster, Sheila A. McIlraith, Jimmy Ba:
You Can't Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments. NeurIPS 2022 - [c126]Mathieu Tuli, Andrew C. Li, Pashootan Vaezipoor, Toryn Q. Klassen, Scott Sanner, Sheila A. McIlraith:
Learning to Follow Instructions in Text-Based Games. NeurIPS 2022 - [c125]Diane Horton, Sheila A. McIlraith, Nina Wang, Maryam Majedi, Emma McClure, Benjamin Wald:
Embedding Ethics in Computer Science Courses: Does it Work? SIGCSE (1) 2022: 481-487 - [i23]Keiran Paster, Sheila A. McIlraith, Jimmy Ba:
You Can't Count on Luck: Why Decision Transformers Fail in Stochastic Environments. CoRR abs/2205.15967 (2022) - [i22]Andrew C. Li, Pashootan Vaezipoor, Rodrigo Toro Icarte, Sheila A. McIlraith:
Challenges to Solving Combinatorially Hard Long-Horizon Deep RL Tasks. CoRR abs/2206.01812 (2022) - [i21]Mathieu Tuli, Andrew C. Li, Pashootan Vaezipoor, Toryn Q. Klassen, Scott Sanner, Sheila A. McIlraith:
Learning to Follow Instructions in Text-Based Games. CoRR abs/2211.04591 (2022) - [i20]Andrew C. Li, Zizhao Chen, Pashootan Vaezipoor, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith:
Noisy Symbolic Abstractions for Deep RL: A case study with Reward Machines. CoRR abs/2211.10902 (2022) - [i19]Fredrik Heintz, Gerhard Lakemeyer, Sheila A. McIlraith:
Cognitive Robotics (Dagstuhl Seminar 22391). Dagstuhl Reports 12(9): 200-219 (2022) - 2021
- [c124]Maayan Shvo, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith:
Interpretable Sequence Classification via Discrete Optimization. AAAI 2021: 9647-9656 - [c123]Maayan Shvo, Zhiming Hu, Rodrigo Toro Icarte, Iqbal Mohomed, Allan D. Jepson, Sheila A. McIlraith:
AppBuddy: Learning to Accomplish Tasks in Mobile Apps via Reinforcement Learning. Canadian AI 2021 - [c122]Pouya Shati, Eldan Cohen, Sheila A. McIlraith:
SAT-Based Approach for Learning Optimal Decision Trees with Non-Binary Features. CP 2021: 50:1-50:16 - [c121]Keiran Paster, Sheila A. McIlraith, Jimmy Ba:
Planning from Pixels using Inverse Dynamics Models. ICLR 2021 - [c120]Pashootan Vaezipoor, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith:
LTL2Action: Generalizing LTL Instructions for Multi-Task RL. ICML 2021: 10497-10508 - [c119]Eldan Cohen, Richard Anthony Valenzano, Sheila A. McIlraith:
Type-WA*: Using Exploration in Bounded Suboptimal Planning. IJCAI 2021: 4047-4053 - [i18]Pashootan Vaezipoor, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith:
LTL2Action: Generalizing LTL Instructions for Multi-Task RL. CoRR abs/2102.06858 (2021) - [i17]Maayan Shvo, Zhiming Hu, Rodrigo Toro Icarte, Iqbal Mohomed, Allan D. Jepson, Sheila A. McIlraith:
AppBuddy: Learning to Accomplish Tasks in Mobile Apps via Reinforcement Learning. CoRR abs/2106.00133 (2021) - [i16]Parand Alizadeh Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith:
Be Considerate: Objectives, Side Effects, and Deciding How to Act. CoRR abs/2106.02617 (2021) - [i15]Christian Muise, Vaishak Belle, Paolo Felli, Sheila A. McIlraith, Tim Miller, Adrian R. Pearce, Liz Sonenberg:
Efficient Multi-agent Epistemic Planning: Teaching Planners About Nested Belief. CoRR abs/2110.02480 (2021) - [i14]Rodrigo Toro Icarte, Ethan Waldie, Toryn Q. Klassen, Richard Anthony Valenzano, Margarita P. Castro, Sheila A. McIlraith:
Learning Reward Machines: A Study in Partially Observable Reinforcement Learning. CoRR abs/2112.09477 (2021) - 2020
- [c118]Maayan Shvo, Sheila A. McIlraith:
Active Goal Recognition. AAAI 2020: 9957-9966 - [c117]León Illanes, Xi Yan, Rodrigo Toro Icarte, Sheila A. McIlraith:
Symbolic Plans as High-Level Instructions for Reinforcement Learning. ICAPS 2020: 540-550 - [c116]Maayan Shvo, Toryn Q. Klassen, Sheila A. McIlraith:
Towards the Role of Theory of Mind in Explanation. EXTRAAMAS@AAMAS 2020: 75-93 - [c115]Maayan Shvo, Toryn Q. Klassen, Shirin Sohrabi, Sheila A. McIlraith:
Epistemic Plan Recognition. AAMAS 2020: 1251-1259 - [c114]Toryn Q. Klassen, Sheila A. McIlraith, Hector J. Levesque:
Changing Beliefs about Domain Dynamics in the Situation Calculus. KR 2020: 572-581 - [i13]Maayan Shvo, Toryn Q. Klassen, Sheila A. McIlraith:
Towards the Role of Theory of Mind in Explanation. CoRR abs/2005.02963 (2020) - [i12]Rodrigo Toro Icarte, Richard Anthony Valenzano, Toryn Q. Klassen, Phillip J. K. Christoffersen, Amir-massoud Farahmand, Sheila A. McIlraith:
The act of remembering: a study in partially observable reinforcement learning. CoRR abs/2010.01753 (2020) - [i11]Maayan Shvo, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith:
Interpretable Sequence Classification via Discrete Optimization. CoRR abs/2010.02819 (2020) - [i10]Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith:
Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning. CoRR abs/2010.03950 (2020) - [i9]Keiran Paster, Sheila A. McIlraith, Jimmy Ba:
Planning from Pixels using Inverse Dynamics Models. CoRR abs/2012.02419 (2020)
2010 – 2019
- 2019
- [c113]León Illanes, Sheila A. McIlraith:
Generalized Planning via Abstraction: Arbitrary Numbers of Objects. AAAI 2019: 7610-7618 - [c112]Alberto Camacho, Meghyn Bienvenu, Sheila A. McIlraith:
Towards a Unified View of AI Planning and Reactive Synthesis. ICAPS 2019: 58-67 - [c111]Alberto Camacho, Sheila A. McIlraith:
Learning Interpretable Models Expressed in Linear Temporal Logic. ICAPS 2019: 621-630 - [c110]Rodrigo Toro Icarte, León Illanes, Margarita P. Castro, André A. Ciré, Sheila A. McIlraith, J. Christopher Beck:
Training Binarized Neural Networks Using MIP and CP. CP 2019: 401-417 - [c109]Alberto Camacho, Sheila A. McIlraith:
Strong Fully Observable Non-Deterministic Planning with LTL and LTLf Goals. IJCAI 2019: 5523-5531 - [c108]Alberto Camacho, Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith:
LTL and Beyond: Formal Languages for Reward Function Specification in Reinforcement Learning. IJCAI 2019: 6065-6073 - [c107]Rodrigo Toro Icarte, Ethan Waldie, Toryn Q. Klassen, Richard Anthony Valenzano, Margarita P. Castro, Sheila A. McIlraith:
Learning Reward Machines for Partially Observable Reinforcement Learning. NeurIPS 2019: 15497-15508 - [i8]Maayan Shvo, Sheila A. McIlraith:
Towards Empathetic Planning. CoRR abs/1906.06436 (2019) - [i7]Alberto Camacho, Sheila A. McIlraith:
Towards Neural-Guided Program Synthesis for Linear Temporal Logic Specifications. CoRR abs/1912.13430 (2019) - 2018
- [j26]Sheila A. McIlraith, Kilian Q. Weinberger, G. Michael Youngblood, Karen L. Myers, Eric Eaton, Michael Wollowski:
A Recap of the AAAI and IAAI 2018 Conferences and the EAAI Symposium. AI Mag. 39(4): 3-16 (2018) - [c106]Alberto Camacho, Jorge A. Baier, Christian J. Muise, Sheila A. McIlraith:
Synthesizing Controllers: On the Correspondence Between LTL Synthesis and Non-deterministic Planning. Canadian AI 2018: 45-59 - [c105]Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith:
Advice-Based Exploration in Model-Based Reinforcement Learning. Canadian AI 2018: 72-83 - [c104]Maayan Shvo, Shirin Sohrabi, Sheila A. McIlraith:
An AI Planning-Based Approach to the Multi-Agent Plan Recognition Problem. Canadian AI 2018: 253-258 - [c103]Alberto Camacho, Jorge A. Baier, Christian J. Muise, Sheila A. McIlraith:
Finite LTL Synthesis as Planning. ICAPS 2018: 29-38 - [c102]Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith:
Teaching Multiple Tasks to an RL Agent using LTL. AAMAS 2018: 452-461 - [c101]Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith:
Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning. ICML 2018: 2112-2121 - [c100]Alberto Camacho, Christian J. Muise, Jorge A. Baier, Sheila A. McIlraith:
LTL Realizability via Safety and Reachability Games. IJCAI 2018: 4683-4691 - [c99]Alberto Camacho, Christian J. Muise, Jorge A. Baier, Sheila A. McIlraith:
SynKit: LTL Synthesis as a Service. IJCAI 2018: 5817-5819 - [c98]Toryn Q. Klassen, Sheila A. McIlraith, Hector J. Levesque:
Specifying Plausibility Levels for Iterated Belief Change in the Situation Calculus. KR 2018: 257-266 - [c97]Alberto Camacho, Meghyn Bienvenu, Sheila A. McIlraith:
Finite LTL Synthesis with Environment Assumptions and Quality Measures. KR 2018: 454-463 - [e4]Sheila A. McIlraith, Kilian Q. Weinberger:
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-18), New Orleans, Louisiana, USA, February 2-7, 2018. AAAI Press 2018 [contents] - [i6]Alberto Camacho, Meghyn Bienvenu, Sheila A. McIlraith:
Finite LTL Synthesis with Environment Assumptions and Quality Measures. CoRR abs/1808.10831 (2018) - 2017
- [c96]Brent Mombourquette, Christian J. Muise, Sheila A. McIlraith:
Logical Filtering and Smoothing: State Estimation in Partially Observable Domains. AAAI 2017: 3613-3621 - [c95]Alberto Camacho, Eleni Triantafillou, Christian J. Muise, Jorge A. Baier, Sheila A. McIlraith:
Non-Deterministic Planning with Temporally Extended Goals: LTL over Finite and Infinite Traces. AAAI 2017: 3716-3724 - [c94]Maayan Shvo, Shirin Sohrabi, Sheila A. McIlraith:
An AI Planning-Based Approach to the Multi-Agent Plan Recognition Problem (Preliminary Report). AAAI Workshops 2017 - [c93]Toryn Q. Klassen, Hector J. Levesque, Sheila A. McIlraith:
Towards Representing What Readers of Fiction Believe. COMMONSENSE 2017 - [c92]Leon Illanes, Sheila A. McIlraith:
Numeric Planning via Abstraction and Policy Guided Search. IJCAI 2017: 4338-4345 - [c91]Alberto Camacho, Oscar Chen, Scott Sanner, Sheila A. McIlraith:
Non-Markovian Rewards Expressed in LTL: Guiding Search Via Reward Shaping. SOCS 2017: 159-160 - [c90]Sheila A. McIlraith:
Plan and Program Synthesis: A New Look at Some Old Problems (Invited Talk). TIME 2017: 3:1-3:1 - [i5]Chitta Baral, Thomas Bolander, Hans van Ditmarsch, Sheila A. McIlraith:
Epistemic Planning (Dagstuhl Seminar 17231). Dagstuhl Reports 7(6): 1-47 (2017) - 2016
- [j25]Christian J. Muise, J. Christopher Beck, Sheila A. McIlraith:
Optimal Partial-Order Plan Relaxation via MaxSAT. J. Artif. Intell. Res. 57: 113-149 (2016) - [c89]Alberto Camacho, Christian J. Muise, Sheila A. McIlraith:
From FOND to Robust Probabilistic Planning: Computing Compact Policies that Bypass Avoidable Deadends. ICAPS 2016: 65-69 - [c88]Alberto Camacho, Sheila A. McIlraith:
Strong-Cyclic Planning when Fairness is Not a Valid Assumption. KnowProS@IJCAI 2016 - [c87]Alberto Camacho, Eleni Triantafillou, Christian J. Muise, Jorge A. Baier, Sheila A. McIlraith:
Non-Deterministic Planning with Temporally Extended Goals: Completing the Story for Finite and Infinite LTL (Amended Version). KnowProS@IJCAI 2016 - [c86]Leon Illanes, Sheila A. McIlraith:
Numeric Planning via Search Space Abstraction. KnowProS@IJCAI 2016 - [c85]Brent Mombourquette, Christian J. Muise, Sheila A. McIlraith:
Belief State Estimation for Planning via Approximate Logical Filtering and Smoothing. KnowProS@IJCAI 2016 - [c84]Roy Luo, Richard Anthony Valenzano, Yi Li, J. Christopher Beck, Sheila A. McIlraith:
Using Metric Temporal Logic to Specify Scheduling Problems. KR 2016: 581-584 - [c83]Young Yoon, Nathan Robinson, Vinod Muthusamy, Sheila A. McIlraith, Hans-Arno Jacobsen:
Planning the transformation of overlays. SAC 2016: 500-507 - [c82]Leon Illanes, Sheila A. McIlraith:
Numeric Planning via Search Space Abstraction (Extended Abstract). SOCS 2016: 133-134 - 2015
- [j24]Stefano V. Albrecht, André da Motta Salles Barreto, Darius Braziunas, David L. Buckeridge, Heriberto Cuayáhuitl, Nina Dethlefs, Markus Endres, Amir-massoud Farahmand, Mark Fox, Lutz Frommberger, Sam Ganzfried, Yolanda Gil, Sébastien Guillet, Lawrence E. Hunter, Arnav Jhala, Kristian Kersting, George Dimitri Konidaris, Freddy Lécué, Sheila A. McIlraith, Sriraam Natarajan, Zeinab Noorian, David Poole, Rémi Ronfard, Alessandro Saffiotti, Arash Shaban-Nejad, Biplav Srivastava, Gerald Tesauro, Rosario Uceda-Sosa, Guy Van den Broeck, Martijn van Otterlo, Byron C. Wallace, Paul Weng, Jenna Wiens, Jie Zhang:
Reports of the AAAI 2014 Conference Workshops. AI Mag. 36(1): 87-98 (2015) - [c81]Christian J. Muise, Vaishak Belle, Paolo Felli, Sheila A. McIlraith, Tim Miller, Adrian R. Pearce, Liz Sonenberg:
Planning Over Multi-Agent Epistemic States: A Classical Planning Approach. AAAI 2015: 3327-3334 - [c80]Torsten Hahmann, Sheila A. McIlraith:
Towards Ontologies in Variation. AAAI Spring Symposia 2015 - [c79]Toryn Q. Klassen, Sheila A. McIlraith, Hector J. Levesque:
Towards Tractable Inference for Resource-Bounded Agents. AAAI Spring Symposia 2015 - [c78]Young Yoon, Nathan Robinson, Vinod Muthusamy, Sheila A. McIlraith, Hans-Arno Jacobsen:
Towards Planning the Transformation of Overlays. ICDCS 2015: 782-783 - 2014
- [j23]Niloofar Razavi, Azadeh Farzan, Sheila A. McIlraith:
Generating effective tests for concurrent programs via AI automated planning techniques. Int. J. Softw. Tools Technol. Transf. 16(1): 49-65 (2014) - [c77]Christian J. Muise, Vaishak Belle, Sheila A. McIlraith:
Computing Contingent Plans via Fully Observable Non-Deterministic Planning. AAAI 2014: 2322-2329 - [c76]Nathan Robinson, Sheila A. McIlraith, David Toman:
Cost-Based Query Optimization via AI Planning. AAAI 2014: 2344-2351 - [c75]Christian J. Muise, Sheila A. McIlraith, Vaishak Belle:
Non-Deterministic Planning With Conditional Effects. ICAPS 2014 - [c74]Franz Baader, Anthony G. Cohn, Georg Gottlob, Sheila A. McIlraith:
Invited Talks. KR 2014 - [c73]Jorge A. Baier, Brent Mombourquette, Sheila A. McIlraith:
Diagnostic Problem Solving via Planning with Ontic and Epistemic Goals. KR 2014 - 2013
- [c72]Sammy Davis-Mendelow, Jorge A. Baier, Sheila A. McIlraith:
Assumption-Based Planning: Generating Plans and Explanations under Incomplete Knowledge. AAAI 2013: 209-216 - [c71]Christian J. Muise, J. Christopher Beck, Sheila A. McIlraith:
Flexible Execution of Partial Order Plans With Temporal Constraints. IJCAI 2013: 2328-2335 - [c70]Marina Gueroussova, Axel Polleres, Sheila A. McIlraith:
SPARQL with Qualitative and Quantitative Preferences. OrdRing@ISWC 2013: 2-8 - [i4]Uri Lerner, Brooks Moses, Maricia Scott, Sheila A. McIlraith, Daphne Koller:
Monitoring a Complez Physical System using a Hybrid Dynamic Bayes Net. CoRR abs/1301.0582 (2013) - 2012
- [c69]Farah Juma, Eric I. Hsu, Sheila A. McIlraith:
Preference-Based Planning via MaxSAT. Canadian AI 2012: 109-120 - [c68]Christian J. Muise, Sheila A. McIlraith, J. Christopher Beck, Eric I. Hsu:
Dsharp: Fast d-DNNF Compilation with sharpSAT. Canadian AI 2012: 356-361 - [c67]Christian J. Muise, Sheila A. McIlraith, J. Christopher Beck:
Improved Non-Deterministic Planning by Exploiting State Relevance. ICAPS 2012 - [c66]Christian J. Muise, Sheila A. McIlraith, J. Christopher Beck:
Optimally Relaxing Partial-Order Plans with MaxSAT. ICAPS 2012 - [e3]Gerhard Brewka, Thomas Eiter, Sheila A. McIlraith:
Principles of Knowledge Representation and Reasoning: Proceedings of the Thirteenth International Conference, KR 2012, Rome, Italy, June 10-14, 2012. AAAI Press 2012, ISBN 978-1-57735-560-1 [contents] - [i3]Christian Fritz, Sheila A. McIlraith:
Generating Optimal Plans in Highly-Dynamic Domains. CoRR abs/1205.2647 (2012) - 2011
- [j22]Leora Morgenstern, Sheila A. McIlraith:
John McCarthy's legacy. Artif. Intell. 175(1): 1-24 (2011) - [j21]Meghyn Bienvenu, Christian Fritz, Sheila A. McIlraith:
Specifying and computing preferred plans. Artif. Intell. 175(7-8): 1308-1345 (2011) - [j20]Sotirios Liaskos, Sheila A. McIlraith, Shirin Sohrabi, John Mylopoulos:
Representing and reasoning about preferences in requirements engineering. Requir. Eng. 16(3): 227-249 (2011) - [c65]Shirin Sohrabi, Jorge A. Baier, Sheila A. McIlraith:
Preferred Explanations: Theory and Generation via Planning. AAAI 2011: 261-267 - [c64]Renée J. Miller, Frank Wm. Tompa, Sheila A. McIlraith, Jacob Slonim, Eric S. K. Yu:
NSERC business intelligence network: selected topics. CASCON 2011: 313-315 - [c63]Christian J. Muise, Sheila A. McIlraith, J. Christopher Beck:
Monitoring the Execution of Partial-Order Plans via Regression. IJCAI 2011: 1975-1982 - 2010
- [c62]Christian J. Muise, Sheila A. McIlraith, J. Christopher Beck, Eric I. Hsu:
Fast d-DNNF Compilation with sharpSAT. Abstraction, Reformulation, and Approximation 2010 - [c61]Vinay K. Chaudhri, Bert Bredeweg, Richard Fikes, Sheila A. McIlraith, Michael P. Wellman:
A Categorization of KR&R Methods for Requirement Analysis of a Query Answering Knowledge Base. FOIS 2010: 158-171 - [c60]Shirin Sohrabi, Jorge A. Baier, Sheila A. McIlraith:
Diagnosis as Planning Revisited. KR 2010 - [c59]Sotirios Liaskos, Sheila A. McIlraith, Shirin Sohrabi, John Mylopoulos:
Integrating Preferences into Goal Models for Requirements Engineering. RE 2010: 135-144 - [c58]