180 citations · 578 across the 40 of their papers we have counts for
5 papers · 1 filter
Crossmodal Attentive Skill Learner
Shayegan Omidshafiei, Dong-Ki Kim, Jason Pazis +1
This paper presents the Crossmodal Attentive Skill Learner (CASL), integrated with the recently-introduced Asynchronous Advantage Option-Critic (A2OC) architecture [Harb et al., 20…
Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions
Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei +2
This paper presents a data-driven approach for multi-robot coordination in partially-observable domains based on Decentralized Partially Observable Markov Decision Processes (Dec-P…
Scalable Accelerated Decentralized Multi-Robot Policy Search in Continuous Observation Spaces
Shayegan Omidshafiei, Christopher Amato, Miao Liu +3
This paper presents the first ever approach for solving \emph{continuous-observation} Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) and their semi-Marko…
Semantic-level Decentralized Multi-Robot Decision-Making using Probabilistic Macro-Observations
Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett +5
Robust environment perception is essential for decision-making on robots operating in complex domains. Intelligent task execution requires principled treatment of uncertainty sourc…
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability
Shayegan Omidshafiei, Jason Pazis, Christopher Amato +2
Many real-world tasks involve multiple agents with partial observability and limited communication. Learning is challenging in these settings due to local viewpoints of agents, whi…