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Reinforcement Learning
DMAR: Decentralized Multi-agent Rollout Algorithm
A new decentralized and online reinforcement learning algorithm for vehicle routing problem in unmapped environments
Jamison Weber
,
Dhanush Giriyan
,
Devendra R. Parkar
,
Andréa Richa
,
Dimitri Bertsekas
PDF
IARPA HAYSTACK - Anamoly Detection
Our team at LabV2(ASU) [collaboration with Leidos Inc.] works on modeling agent movements in real-world maps. We use knowledge graphs to model the maps in combination with symbolic rule learning and heuristic based graph traversal algorithms to model and learn agent trajectories(both anamolous and normal).
PyReason-Gym: Symbolic logic simulator for Reinforcement Learning
A temporal and annotated-logic based simulation proxy that enables interpretable reinforcement learning
Kaustuv Mukherji
,
Devendra R. Parkar
,
Lahari Pokala
,
Dyuman Aditya
,
Paulo Shakarian
,
Clark Dorman
PDF
Code
Scalable Semantic Non-Markovian Simulation Proxy for Reinforcement Learning [In Press]
A temporal and annotated-logic based simulation proxy that enables interpretable reinforcement learning
[Accepted at International Conference on Semantic Computing]
Kaustuv Mukherji
,
Devendra R. Parkar
,
Lahari Pokala
,
Dyuman Aditya
,
Paulo Shakarian
,
Clark Dorman
Project
Video
DOI
Distributed Online Rollout for Multivehicle Routing in Unmapped Environments [In Press]
We propose a new decentralized and online reinforcement learning algorithm for vehicle routing in a more challenging unmapped environments with provable guarantees of cost improvements over greedy base policy.
[Accepted at International Conference on Autonomous Agents and Multiagent Systems]
Jamison Weber
,
Dhanush Giriyan
,
Devendra R. Parkar
,
Andréa Richa
,
Dimitri Bertsekas
Project
DOI
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