M
Manuela Veloso
Researcher at Carnegie Mellon University
Publications - 738
Citations - 29943
Manuela Veloso is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Robot & Mobile robot. The author has an hindex of 71, co-authored 720 publications receiving 27543 citations. Previous affiliations of Manuela Veloso include University of Pittsburgh & Boğaziçi University.
Papers
More filters
Proceedings ArticleDOI
Risk-Sensitive Reinforcement Learning: a Martingale Approach to Reward Uncertainty
TL;DR: A new decomposition of the randomness contained in the cumulative reward is presented based on the Doob decomposing of a stochastic process, and a new conceptual tool - the \textit{chaotic variation} - is introduced which can rigorously be interpreted as the risk measure of the martingale component associated to the cumulative rewards process.
Proceedings ArticleDOI
A Robot’s Expressive Language Affects Human Strategy and Perceptions in a Competitive Game
Aaron M. Roth,Samantha Reig,Umang Bhatt,Jonathan Shulgach,Tamara Amin,Afsaneh Doryab,Fei Fang,Manuela Veloso +7 more
TL;DR: This article explored human-robot relationships in the context of a competitive Stackelberg Security Game and found that a robot opponent that makes discouraging comments causes a human to play a game less rationally and to perceive the robot more negatively.
Proceedings Article
Trajectory-Based Short-Sighted Probabilistic Planning
TL;DR: In this paper, the authors introduce trajectory-based shortsighted stochastic shortest path problems (SSPs), a novel approach to manage uncertainty for probabilistic planning problems in which states reachable with low probability are substituted by artificial goals that heuristically estimate their cost to reach a goal state.
Using Perception Information for Robot Planning and Execution
Karen Zita Haigh,Manuela Veloso +1 more
TL;DR: ROGUE’s capabilities in executing and processing perception information, including: (1) the generation and execution a plan which requires observation to make informed planning decisions, and (2) the monitoring execution for informed replanning.