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Shlomo Zilberstein
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- affiliation: University of Massachusetts Amherst, USA
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2020 – today
- 2024
- [c196]Saaduddin Mahmud, Marcell Vazquez-Chanlatte, Stefan J. Witwicki, Shlomo Zilberstein:
Explaining the Behavior of POMDP-based Agents Through the Impact of Counterfactual Information. AAMAS 2024: 1346-1354 - [c195]Shuwa Miura, Shlomo Zilberstein:
Observer-Aware Planning with Implicit and Explicit Communication. AAMAS 2024: 1409-1417 - [c194]Moumita Choudhury, Sandhya Saisubramanian, Hao Zhang, Shlomo Zilberstein:
Minimizing Negative Side Effects in Cooperative Multi-Agent Systems using Distributed Coordination. AAMAS 2024: 2213-2215 - [c193]Moumita Choudhury, Sandhya Saisubramanian, Hao Zhang, Shlomo Zilberstein:
Minimizing Negative Side Effects in Cooperative Multi-Agent Systems using Distributed Coordination. FLAIRS 2024 - [c192]Samer B. Nashed, Roderic A. Grupen, Shlomo Zilberstein:
Choosing the Right Tool for the Job: Online Decision Making over SLAM Algorithms. ICRA 2024: 4619-4625 - [c191]Qingyuan Lu, Justin Svegliato, Samer B. Nashed, Shlomo Zilberstein, Stuart Russell:
Ethically Compliant Autonomous Systems under Partial Observability. ICRA 2024: 16229-16235 - [i35]Saaduddin Mahmud, Mason Nakamura, Shlomo Zilberstein:
MAPLE: A Framework for Active Preference Learning Guided by Large Language Models. CoRR abs/2412.07207 (2024) - 2023
- [j44]Connor Basich
, Justin Svegliato, Kyle Hollins Wray, Stefan J. Witwicki, Joydeep Biswas, Shlomo Zilberstein:
Competence-aware systems. Artif. Intell. 316: 103844 (2023) - [c190]Saaduddin Mahmud, Sandhya Saisubramanian, Shlomo Zilberstein:
REVEALE: Reward Verification and Learning Using Explanations. SafeAI@AAAI 2023 - [c189]Aishwarya Srivastava, Sandhya Saisubramanian, Praveen Paruchuri, Akshat Kumar, Shlomo Zilberstein:
Planning and Learning for Non-markovian Negative Side Effects Using Finite State Controllers. AAAI 2023: 15144-15151 - [c188]Saaduddin Mahmud, Connor Basich, Shlomo Zilberstein:
Semi-Autonomous Systems with Contextual Competence Awareness. AAMAS 2023: 689-697 - [c187]Samer B. Nashed, Saaduddin Mahmud, Claudia V. Goldman, Shlomo Zilberstein:
Causal Explanations for Sequential Decision Making Under Uncertainty. AAMAS 2023: 2307-2309 - [c186]Saaduddin Mahmud, Samer B. Nashed, Claudia V. Goldman, Shlomo Zilberstein:
Estimating Causal Responsibility for Explaining Autonomous Behavior. EXTRAAMAS 2023: 78-94 - [c185]Saaduddin Mahmud, Sandhya Saisubramanian, Shlomo Zilberstein:
Explanation-Guided Reward Alignment. IJCAI 2023: 473-482 - [c184]Connor Basich, Saaduddin Mahmud, Shlomo Zilberstein:
Learning Constraints on Autonomous Behavior from Proactive Feedback. IROS 2023: 3680-3687 - [c183]Mason Nakamura, Justin Svegliato, Samer B. Nashed, Shlomo Zilberstein, Stuart Russell:
Formal Composition of Robotic Systems as Contract Programs. IROS 2023: 6727-6732 - [i34]Abhinav Bhatia, Samer B. Nashed, Shlomo Zilberstein:
RL3: Boosting Meta Reinforcement Learning via RL inside RL2. CoRR abs/2306.15909 (2023) - 2022
- [j43]Samer B. Nashed, Shlomo Zilberstein:
A Survey of Opponent Modeling in Adversarial Domains. J. Artif. Intell. Res. 73: 277-327 (2022) - [j42]Sandhya Saisubramanian, Ece Kamar, Shlomo Zilberstein:
Avoiding Negative Side Effects of Autonomous Systems in the Open World. J. Artif. Intell. Res. 74: 143-177 (2022) - [j41]Sadegh Rabiee
, Connor Basich, Kyle Hollins Wray, Shlomo Zilberstein, Joydeep Biswas
:
Competence-Aware Path Planning Via Introspective Perception. IEEE Robotics Autom. Lett. 7(2): 3218-3225 (2022) - [c182]Abhinav Bhatia, Justin Svegliato, Samer B. Nashed, Shlomo Zilberstein:
Tuning the Hyperparameters of Anytime Planning: A Metareasoning Approach with Deep Reinforcement Learning. ICAPS 2022: 556-564 - [c181]Justin Svegliato, Connor Basich, Sandhya Saisubramanian, Shlomo Zilberstein:
Metareasoning for Safe Decision Making in Autonomous Systems. ICRA 2022: 11073-11079 - [c180]Connor Basich, Joseph A. Russino, Steve A. Chien, Shlomo Zilberstein:
A Sampling Based Approach to Robust Planning for a Planetary Lander. IROS 2022: 4106-4111 - [c179]Connor Basich, John R. Peterson
, Shlomo Zilberstein:
Planning with Intermittent State Observability: Knowing When to Act Blind. IROS 2022: 11657-11664 - [c178]Samer B. Nashed, Justin Svegliato, Abhinav Bhatia, Stuart Russell, Shlomo Zilberstein:
Selecting the Partial State Abstractions of MDPs: A Metareasoning Approach with Deep Reinforcement Learning. IROS 2022: 11665-11670 - [c177]Shuwa Miura, Kyle Hollins Wray, Shlomo Zilberstein:
Heuristic Search for SSPs with Lexicographic Preferences over Multiple Costs. SOCS 2022: 127-135 - [c176]John R. Peterson
, Anagha Kulkarni, Emil Keyder, Joseph Kim, Shlomo Zilberstein:
Trajectory Constraint Heuristics for Optimal Probabilistic Planning. SOCS 2022: 153-161 - [i33]Samer B. Nashed, Saaduddin Mahmud, Claudia V. Goldman, Shlomo Zilberstein:
A Unifying Framework for Causal Explanation of Sequential Decision Making. CoRR abs/2205.15462 (2022) - [i32]Emily Pruc, Shlomo Zilberstein, Joydeep Biswas:
Dense Crowd Flow-Informed Path Planning. CoRR abs/2206.00705 (2022) - [i31]Abhinav Bhatia, Philip S. Thomas, Shlomo Zilberstein:
Adaptive Rollout Length for Model-Based RL Using Model-Free Deep RL. CoRR abs/2206.02380 (2022) - 2021
- [j40]Sandhya Saisubramanian, Shlomo Zilberstein, Ece Kamar:
Avoiding Negative Side Effects Due to Incomplete Knowledge of AI Systems. AI Mag. 42(4): 62-71 (2021) - [c175]Justin Svegliato, Samer B. Nashed, Shlomo Zilberstein:
Ethically Compliant Sequential Decision Making. AAAI 2021: 11657-11665 - [c174]Samer B. Nashed, Justin Svegliato, Shlomo Zilberstein:
Ethically Compliant Planning within Moral Communities. AIES 2021: 188-198 - [c173]Sainyam Galhotra, Sandhya Saisubramanian, Shlomo Zilberstein:
Learning to Generate Fair Clusters from Demonstrations. AIES 2021: 491-501 - [c172]Sandhya Saisubramanian, Shlomo Zilberstein:
Mitigating Negative Side Effects via Environment Shaping. AAMAS 2021: 1640-1642 - [c171]Sandhya Saisubramanian, Shannon C. Roberts
, Shlomo Zilberstein:
Understanding User Attitudes Towards Negative Side Effects of AI Systems. CHI Extended Abstracts 2021: 368:1-368:6 - [c170]Samer B. Nashed, Justin Svegliato, Matteo Brucato, Connor Basich, Rod Grupen, Shlomo Zilberstein:
Solving Markov Decision Processes with Partial State Abstractions. ICRA 2021: 813-819 - [c169]Connor Basich, Justin Svegliato, Allyson Beach, Kyle Hollins Wray, Stefan J. Witwicki, Shlomo Zilberstein:
Improving Competence via Iterative State Space Refinement. IROS 2021: 1865-1871 - [c168]Shane Parr, Ishan Khatri, Justin Svegliato, Shlomo Zilberstein:
Agent-Aware State Estimation in Autonomous Vehicles. IROS 2021: 6694-6699 - [c167]Shuwa Miura
, Andrew L. Cohen, Shlomo Zilberstein:
Maximizing Legibility in Stochastic Environments. RO-MAN 2021: 1053-1059 - [c166]Abhinav Bhatia, Justin Svegliato, Shlomo Zilberstein:
On the Benefits of Randomly Adjusting Anytime Weighted A. SOCS 2021: 116-120 - [c165]Shuwa Miura, Shlomo Zilberstein:
A unifying framework for observer-aware planning and its complexity. UAI 2021: 610-620 - [i30]Sainyam Galhotra, Sandhya Saisubramanian, Shlomo Zilberstein:
Learning to Generate Fair Clusters from Demonstrations. CoRR abs/2102.03977 (2021) - [i29]Sandhya Saisubramanian, Shlomo Zilberstein:
Mitigating Negative Side Effects via Environment Shaping. CoRR abs/2102.07017 (2021) - [i28]Shane Parr, Ishan Khatri, Justin Svegliato, Shlomo Zilberstein:
Agent-aware State Estimation in Autonomous Vehicles. CoRR abs/2108.00366 (2021) - [i27]Sadegh Rabiee, Connor Basich, Kyle Hollins Wray, Shlomo Zilberstein, Joydeep Biswas:
Competence-Aware Path Planning via Introspective Perception. CoRR abs/2109.13974 (2021) - 2020
- [c164]Sandhya Saisubramanian, Sainyam Galhotra, Shlomo Zilberstein
:
Balancing the Tradeoff Between Clustering Value and Interpretability. AIES 2020: 351-357 - [c163]Connor Basich, Justin Svegliato, Kyle Hollins Wray, Stefan J. Witwicki, Joydeep Biswas, Shlomo Zilberstein:
Learning to Optimize Autonomy in Competence-Aware Systems. AAMAS 2020: 123-131 - [c162]Shuwa Miura, Shlomo Zilberstein:
Maximizing Plan Legibility in Stochastic Environments. AAMAS 2020: 1931-1933 - [c161]Sandhya Saisubramanian, Ece Kamar, Shlomo Zilberstein:
Mitigating the Negative Side Effects of Reasoning with Imperfect Models: A Multi-Objective Approach. AAMAS 2020: 1984-1986 - [c160]Aritra Ghosh
, Beverly P. Woolf, Shlomo Zilberstein, Andrew S. Lan:
Skill-based Career Path Modeling and Recommendation. IEEE BigData 2020: 1156-1165 - [c159]Christabel Wayllace, Sarah Keren, Avigdor Gal, Erez Karpas, William Yeoh
, Shlomo Zilberstein:
Accounting for Observer's Partial Observability in Stochastic Goal Recognition Design. ECAI 2020: 2394-2401 - [c158]Justin Svegliato, Samer B. Nashed, Shlomo Zilberstein:
An Integrated Approach to Moral Autonomous Systems. ECAI 2020: 2941-2942 - [c157]Justin Svegliato, Prakhar Sharma, Shlomo Zilberstein:
A Model-Free Approach to Meta-Level Control of Anytime Algorithms. ICRA 2020: 11436-11442 - [c156]Sandhya Saisubramanian, Ece Kamar, Shlomo Zilberstein:
A Multi-Objective Approach to Mitigate Negative Side Effects. IJCAI 2020: 354-361 - [c155]Justin Svegliato, Samer B. Nashed, Shlomo Zilberstein:
Ethically Compliant Planning in Moral Autonomous Systems. AISafety@IJCAI 2020 - [c154]Feng Wu
, Shlomo Zilberstein, Nicholas R. Jennings:
Multi-agent Planning with High-Level Human Guidance. PRIMA 2020: 182-198 - [c153]Connor Basich, Justin Svegliato, Kyle Hollins Wray, Stefan J. Witwicki, Shlomo Zilberstein:
Improving Competence for Reliable Autonomy. AREA@ECAI 2020: 37-53 - [i26]Connor Basich, Justin Svegliato, Kyle Hollins Wray, Stefan J. Witwicki, Joydeep Biswas, Shlomo Zilberstein:
Learning to Optimize Autonomy in Competence-Aware Systems. CoRR abs/2003.07745 (2020) - [i25]Sandhya Saisubramanian, Shlomo Zilberstein, Ece Kamar:
Avoiding Negative Side Effects due to Incomplete Knowledge of AI Systems. CoRR abs/2008.12146 (2020) - [i24]Richard G. Freedman, Steven J. Levine, Brian C. Williams, Shlomo Zilberstein:
Helpfulness as a Key Metric of Human-Robot Collaboration. CoRR abs/2010.04914 (2020)
2010 – 2019
- 2019
- [j39]Aaron Adler, Prithviraj Dasgupta, Nick DePalma, Mohammed Eslami, Richard G. Freedman, John E. Laird
, Christian Lebiere, Katrin S. Lohan, Ross Mead, Mark Roberts, Paul S. Rosenbloom, Emmanuel Senft, Frank Stein, Tom Williams, Kyle Hollins Wray, Fusun Yaman, Shlomo Zilberstein
:
Reports of the 2018 AAAI Fall Symposium. AI Mag. 40(2): 66-72 (2019) - [j38]Luis Enrique Pineda, Shlomo Zilberstein:
Probabilistic Planning with Reduced Models. J. Artif. Intell. Res. 65: 271-306 (2019) - [c152]Sandhya Saisubramanian, Shlomo Zilberstein:
Minimizing the Negative Side Effects of Planning with Reduced Models. SafeAI@AAAI 2019 - [c151]Sarah Keren, Luis Enrique Pineda, Avigdor Gal, Erez Karpas, Shlomo Zilberstein:
Efficient Heuristic Search for Optimal Environment Redesign. ICAPS 2019: 246-254 - [c150]Luis Enrique Pineda, Shlomo Zilberstein:
Soft Labeling in Stochastic Shortest Path Problems. AAMAS 2019: 467-475 - [c149]Kyle Hollins Wray, Shlomo Zilberstein:
Policy Networks: A Framework for Scalable Integration of Multiple Decision-Making Models. AAMAS 2019: 2270-2272 - [c148]Feng Wu
, Shlomo Zilberstein
, Nicholas R. Jennings:
Stochastic multi-agent planning with partial state models. DAI 2019: 1:1-1:8 - [c147]Abhishek Dwaraki, Richard G. Freedman, Shlomo Zilberstein
, Tilman Wolf:
Using Natural Language Constructs and Concepts to Aid Network Management. ICNC 2019: 802-808 - [c146]Kyle Hollins Wray, Shlomo Zilberstein
:
Generalized Controllers in POMDP Decision-Making. ICRA 2019: 7166-7172 - [c145]Justin Svegliato, Kyle Hollins Wray, Stefan J. Witwicki, Joydeep Biswas
, Shlomo Zilberstein
:
Belief Space Metareasoning for Exception Recovery. IROS 2019: 1224-1229 - [c144]Sandhya Saisubramanian, Kyle Hollins Wray, Luis Enrique Pineda, Shlomo Zilberstein
:
Planning in Stochastic Environments with Goal Uncertainty. IROS 2019: 1649-1654 - [c143]Sandhya Saisubramanian, Shlomo Zilberstein:
Adaptive Outcome Selection for Planning with Reduced Models. IROS 2019: 1655-1660 - [c142]Sandhya Saisubramanian, Connor Basich, Shlomo Zilberstein
, Claudia V. Goldman:
Satisfying Social Preferences in Ridesharing Services. ITSC 2019: 3720-3725 - [i23]Sainyam Galhotra, Sandhya Saisubramanian, Shlomo Zilberstein:
Lexicographically Ordered Multi-Objective Clustering. CoRR abs/1903.00750 (2019) - [i22]Sandhya Saisubramanian, Shlomo Zilberstein:
Minimizing the Negative Side Effects of Planning with Reduced Models. CoRR abs/1905.09355 (2019) - [i21]Richard G. Freedman, Yi Ren Fung, Roman Ganchin, Shlomo Zilberstein:
Responsive Planning and Recognition for Closed-Loop Interaction. CoRR abs/1909.06427 (2019) - [i20]Sandhya Saisubramanian, Sainyam Galhotra, Shlomo Zilberstein:
Balancing the Tradeoff Between Clustering Value and Interpretability. CoRR abs/1912.07820 (2019) - 2018
- [c141]Richard Gabriel Freedman, Shlomo Zilberstein:
Roles that Plan, Activity, and Intent Recognition with Planning Can Play in Games. AAAI Workshops 2018: 547-551 - [c140]Richard G. Freedman, Yi Ren Fung, Roman Ganchin, Shlomo Zilberstein:
Towards Quicker Probabilistic Recognition with Multiple Goal Heuristic Search. AAAI Workshops 2018: 601-606 - [c139]Kyle Hollins Wray, Akshat Kumar, Shlomo Zilberstein:
Integrated Cooperation and Competition in Multi-Agent Decision-Making. AAAI 2018: 4751-4758 - [c138]Feng Wu, Shlomo Zilberstein, Xiaoping Chen:
Privacy-Preserving Policy Iteration for Decentralized POMDPs. AAAI 2018: 4759-4766 - [c137]Sandhya Saisubramanian, Shlomo Zilberstein, Prashant J. Shenoy:
Planning Using a Portfolio of Reduced Models. AAMAS 2018: 2057-2059 - [c136]Justin Svegliato, Kyle Hollins Wray, Shlomo Zilberstein:
Meta-Level Control of Anytime Algorithms with Online Performance Prediction. IJCAI 2018: 1499-1505 - [i19]Siddharth Srivastava, Nishant Desai, Richard G. Freedman, Shlomo Zilberstein:
An Anytime Algorithm for Task and Motion MDPs. CoRR abs/1802.05835 (2018) - [i18]Sandhya Saisubramanian, Kyle Hollins Wray, Luis Enrique Pineda, Shlomo Zilberstein:
Planning in Stochastic Environments with Goal Uncertainty. CoRR abs/1810.08159 (2018) - 2017
- [c135]Luis Enrique Pineda, Kyle Hollins Wray, Shlomo Zilberstein:
Fast SSP Solvers Using Short-Sighted Labeling. AAAI 2017: 3629-3635 - [c134]XiaoJian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein:
Robust Optimization for Tree-Structured Stochastic Network Design. AAAI 2017: 4545-4551 - [c133]Richard G. Freedman, Shlomo Zilberstein:
Integration of Planning with Recognition for Responsive Interaction Using Classical Planners. AAAI 2017: 4581-4588 - [c132]Sarah Keren, Avigdor Gal, Erez Karpas, Luis Enrique Pineda, Shlomo Zilberstein:
Redesigning Stochastic Environments for Maximized Utility. AAAI 2017: 4947-4948 - [c131]Sarah Keren, Luis Enrique Pineda, Avigdor Gal, Erez Karpas, Shlomo Zilberstein:
Redesigning Stochastic Environments for Maximized Utility. AAAI Workshops 2017 - [c130]Richard G. Freedman, Shlomo Zilberstein:
Does the Human's Representation Matter for Unsupervised Activity Recognition? AAAI Fall Symposia 2017: 94-98 - [c129]Haochong Zhang, Rongyun Cao, Shlomo Zilberstein
, Feng Wu
, Xiaoping Chen:
Toward Effective Soft Robot Control via Reinforcement Learning. ICIRA (1) 2017: 173-184 - [c128]Feng Wu
, Shlomo Zilberstein, Xiaoping Chen:
Multi-Agent Planning with Baseline Regret Minimization. IJCAI 2017: 444-450 - [c127]Sarah Keren, Luis Enrique Pineda, Avigdor Gal, Erez Karpas
, Shlomo Zilberstein:
Equi-Reward Utility Maximizing Design in Stochastic Environments. IJCAI 2017: 4353-4360 - [c126]Kyle Hollins Wray, Stefan J. Witwicki, Shlomo Zilberstein:
Online Decision-Making for Scalable Autonomous Systems. IJCAI 2017: 4768-4774 - [c125]Kyle Hollins Wray, Shlomo Zilberstein
:
Approximating reachable belief points in POMDPs. IROS 2017: 117-122 - [i17]Luis Enrique Pineda, Shlomo Zilberstein:
Generalizing the Role of Determinization in Probabilistic Planning. CoRR abs/1705.07381 (2017) - 2016
- [c124]Kyle Hollins Wray, Shlomo Zilberstein:
A POMDP Formulation of Proactive Learning. AAAI 2016: 3202-3208 - [c123]XiaoJian Wu, Daniel Sheldon, Shlomo Zilberstein:
Optimizing Resilience in Large Scale Networks. AAAI 2016: 3922-3928 - [c122]Richard G. Freedman, Shlomo Zilberstein:
Safety in AI-HRI: Challenges Complementing User Experience Quality. AAAI Fall Symposia 2016 - [c121]Akshat Kumar, Hala Mostafa, Shlomo Zilberstein:
Dual Formulations for Optimizing Dec-POMDP Controllers. ICAPS 2016: 202-210 - [c120]Kyle Hollins Wray, Luis Enrique Pineda, Shlomo Zilberstein:
Hierarchical Approach to Transfer of Control in Semi-Autonomous Systems: (Extended Abstract). AAMAS 2016: 1285-1286 - [c119]Kyle Hollins Wray, Luis Enrique Pineda, Shlomo Zilberstein:
Hierarchical Approach to Transfer of Control in Semi-Autonomous Systems. IJCAI 2016: 517-523 - [c118]Kyle Hollins Wray, Dirk Ruiken
, Roderic A. Grupen, Shlomo Zilberstein
:
Log-space harmonic function path planning. IROS 2016: 1511-1516 - [i16]XiaoJian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein:
Robust Optimization for Tree-Structured Stochastic Network Design. CoRR abs/1612.00104 (2016) - 2015
- [j37]Akshat Kumar, Shlomo Zilberstein, Marc Toussaint:
Probabilistic Inference Techniques for Scalable Multiagent Decision Making. J. Artif. Intell. Res. 53: 223-270 (2015) - [c117]Siddharth Srivastava, Shlomo Zilberstein, Abhishek Gupta, Pieter Abbeel, Stuart Russell:
Tractability of Planning with Loops. AAAI 2015: 3393-3401 - [c116]Kyle Hollins Wray, Shlomo Zilberstein, Abdel-Illah Mouaddib:
Multi-Objective MDPs with Conditional Lexicographic Reward Preferences. AAAI 2015: 3418-3424 - [c115]Shlomo Zilberstein:
Building Strong Semi-Autonomous Systems. AAAI 2015: 4088-4092 - [c114]Richard G. Freedman, Hee-Tae Jung, Shlomo Zilberstein:
Temporal and Object Relations in Unsupervised Plan and Activity Recognition. AAAI Fall Symposia 2015: 51-59 - [c113]Luis Enrique Pineda, Kyle Hollins Wray, Shlomo Zilberstein:
Revisiting Multi-Objective MDPs with Relaxed Lexicographic Preferences. AAAI Fall Symposia 2015: 63-68 - [c112]Kyle Hollins Wray, Shlomo Zilberstein:
A Parallel Point-Based POMDP Algorithm Leveraging GPUs. AAAI Fall Symposia 2015: 95-96 - [c111]Akshat Kumar, Shlomo Zilberstein:
History-Based Controller Design and Optimization for Partially Observable MDPs. ICAPS 2015: 156-164 - [c110]Luis Enrique Pineda, Takeshi Takahashi, Hee-Tae Jung, Shlomo Zilberstein
, Roderic A. Grupen:
Continual planning for search and rescue robots. Humanoids 2015: 243-248 - [c109]Kyle Hollins Wray, Shlomo Zilberstein:
Multi-Objective POMDPs with Lexicographic Reward Preferences. IJCAI 2015: 1719-1725 - [c108]XiaoJian Wu, Daniel Sheldon, Shlomo Zilberstein:
Fast Combinatorial Algorithm for Optimizing the Spread of Cascades. IJCAI 2015: 2655-2661 - [c107]Hee-Tae Jung, Richard G. Freedman, Tammie Foster, Yu-Kyong Choe, Shlomo Zilberstein
, Roderic A. Grupen:
Learning Therapy Strategies from Demonstration Using Latent Dirichlet Allocation. IUI 2015: 432-436 - [e2]Ronen I. Brafman, Carmel Domshlak, Patrik Haslum, Shlomo Zilberstein:
Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling, ICAPS 2015, Jerusalem, Israel, June 7-11, 2015. AAAI Press 2015, ISBN 978-1-57735-731-5 [contents] - 2014
- [c106]XiaoJian Wu, Daniel Sheldon, Shlomo Zilberstein:
Rounded Dynamic Programming for Tree-Structured Stochastic Network Design. AAAI 2014: 479-485 - [c105]Duc Thien Nguyen, William Yeoh, Hoong Chuin Lau, Shlomo Zilberstein, Chongjie Zhang:
Decentralized Multi-Agent Reinforcement Learning in Average-Reward Dynamic DCOPs. AAAI 2014: 1447-1455 - [c104]Richard Gabriel Freedman, Hee-Tae Jung, Shlomo Zilberstein:
Temporal and Object Relations in Plan and Activity Recognition for Robots Using Topic Models. AAAI Fall Symposia 2014 - [c103]Richard G. Freedman, Hee-Tae Jung, Shlomo Zilberstein:
Plan and Activity Recognition from a Topic Modeling Perspective. ICAPS 2014 - [c102]Luis Enrique Pineda, Shlomo Zilberstein:
Planning Under Uncertainty Using Reduced Models: Revisiting Determinization. ICAPS 2014 - [c101]Duc Thien Nguyen, William Yeoh, Hoong Chuin Lau, Shlomo Zilberstein, Chongjie Zhang:
Decentralized multi-agent reinforcement learning in average-reward dynamic DCOPs. AAMAS 2014: 1341-1342 - [c100]