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20122026
most citedTrajectory Distribution Control for Model Predictive Path Integral Control using Covariance Steering

61 citations · 243 across the 64 of their papers we have counts for

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Showing 2020Show all

13 papers · 1 filter

cs.RO2020

A Generalized A* Algorithm for Finding Globally Optimal Paths in Weighted Colored Graphs

Jaein Lim, Panagiotis Tsiotras

Both geometric and semantic information of the search space is imperative for a good plan. We encode those properties in a weighted colored graph (geometric information in terms of…

math.OC2020

Covariance Steering with Optimal Risk Allocation

Joshua Pilipovsky, Panagiotis Tsiotras

This paper extends the optimal covariance steering problem for linear stochastic systems subject to chance constraints to account for optimal risk allocation. Previous works have a…

cs.LG2020★ 2 cited

Learning Nash Equilibria in Zero-Sum Stochastic Games via Entropy-Regularized Policy Approximation

Yue Guan, Qifan Zhang, Panagiotis Tsiotras

We explore the use of policy approximations to reduce the computational cost of learning Nash equilibria in zero-sum stochastic games. We propose a new Q-learning type algorithm th…

math.OC2020★ 10 cited

Apollonius Allocation Algorithm for Heterogeneous Pursuers to Capture Multiple Evaders

Venkata Ramana Makkapati, Panagiotis Tsiotras

In this paper, we address pursuit-evasion problems involving multiple pursuers and multiple evaders. The pursuer and the evader teams are assumed to be heterogeneous, in the sense…

math.OC2020

Forward-Backward Rapidly-Exploring Random Trees for Stochastic Optimal Control

Kelsey P. Hawkins, Ali Pakniyat, Evangelos Theodorou +1

We propose a numerical method for the computation of the forward-backward stochastic differential equations (FBSDE) appearing in the Feynman-Kac representation of the value functio…

cs.RO2020★ 15 cited

Information-Theoretic Abstractions for Planning in Agents with Computational Constraints

Daniel T. Larsson, Dipankar Maity, Panagiotis Tsiotras

In this paper, we develop a framework for path-planning on abstractions that are not provided to the agent a priori but instead emerge as a function of the available computational…