
Agentaware State Estimation in Autonomous Vehicles
Autonomous systems often operate in environments where the behavior of m...
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Mitigating Negative Side Effects via Environment Shaping
Agents operating in unstructured environments often produce negative sid...
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Learning to Generate Fair Clusters from Demonstrations
Fair clustering is the process of grouping similar entities together, wh...
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Helpfulness as a Key Metric of HumanRobot Collaboration
As robotic teammates become more common in society, people will assess t...
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Avoiding Negative Side Effects due to Incomplete Knowledge of AI Systems
Autonomous agents acting in the realworld often operate based on models...
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Improving Competence for Reliable Autonomy
Given the complexity of realworld, unstructured domains, it is often im...
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Learning to Optimize Autonomy in CompetenceAware Systems
Interest in semiautonomous systems (SAS) is growing rapidly as a paradi...
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Balancing the Tradeoff Between Clustering Value and Interpretability
Graph clustering groups entities – the vertices of a graph – based on th...
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Responsive Planning and Recognition for ClosedLoop Interaction
Many intelligent systems currently interact with others using at least o...
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Minimizing the Negative Side Effects of Planning with Reduced Models
Reduced models of large Markov decision processes accelerate planning by...
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Lexicographically Ordered MultiObjective Clustering
We introduce a rich model for multiobjective clustering with lexicograp...
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Planning in Stochastic Environments with Goal Uncertainty
We present the Goal Uncertain Stochastic Shortest Path (GUSSP) problem ...
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An Anytime Algorithm for Task and Motion MDPs
Integrated task and motion planning has emerged as a challenging problem...
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Generalizing the Role of Determinization in Probabilistic Planning
The stochastic shortest path problem (SSP) is a highly expressive model ...
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Robust Optimization for TreeStructured Stochastic Network Design
Stochastic network design is a general framework for optimizing network ...
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A Bilinear Programming Approach for Multiagent Planning
Multiagent planning and coordination problems are common and known to be...
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Policy Iteration for Decentralized Control of Markov Decision Processes
Coordination of distributed agents is required for problems arising in m...
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The Complexity of Decentralized Control of Markov Decision Processes
Planning for distributed agents with partial state information is consid...
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Symbolic Generalization for Online Planning
Symbolic representations have been used successfully in offline plannin...
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RegionBased Incremental Pruning for POMDPs
We present a major improvement to the incremental pruning algorithm for ...
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MAA*: A Heuristic Search Algorithm for Solving Decentralized POMDPs
We present multiagent A* (MAA*), the first complete and optimal heurist...
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Rollout Sampling Policy Iteration for Decentralized POMDPs
We present decentralized rollout sampling policy iteration (DecRSPI)  a...
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Anytime Planning for Decentralized POMDPs using Expectation Maximization
Decentralized POMDPs provide an expressive framework for multiagent seq...
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MessagePassing Algorithms for Quadratic Programming Formulations of MAP Estimation
Computing maximum a posteriori (MAP) estimation in graphical models is a...
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CommunicationBased Decomposition Mechanisms for Decentralized MDPs
Multiagent planning in stochastic environments can be framed formally a...
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Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes
Approximate dynamic programming has been used successfully in a large va...
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Shlomo Zilberstein
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Professor of Computer Science and Associate Dean at the University of Massachusetts Amherst