Lessons Learned from the CYK Algorithm for Parsing-based Verification of Hierarchical Plans
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023 Verification of hierarchical plans deals with the problem of whether an action sequence is causally consistent and can be obtained by a decomposition of a goal task.
Simona Ondrčková +3 more
doaj +1 more source
A Safe Hierarchical Planning Framework for Complex Driving Scenarios based on Reinforcement Learning [PDF]
IEEE International Conference on Robotics and Automation, 2021 Autonomous vehicles need to handle various traffic conditions and make safe and efficient decisions and maneuvers. However, on the one hand, a single optimization/sampling-based motion planner cannot efficiently generate safe trajectories in real time ...
Jinning Li +3 more
semanticscholar +1 more source
Towards a Sustainable Power Grid: Stochastic Hierarchical Planning for High Renewable Integration [PDF]
European Journal of Operational Research, 2021 Driven by ambitious renewable portfolio standards, large scale inclusion of variable energy resources (such as wind and solar) are expected to introduce unprecedented levels of uncertainty into power system operations.
Semih Atakan +2 more
semanticscholar +1 more source
The Application of “Big Data Analysis + Hierarchical Medical” Model in the Context of the COVID-19 [PDF]
E3S Web of Conferences, 2021 The COVID-19 epidemic has swept the world, causing serious impact and influence on economic development and residents' life in countries all over the world.
Yang Xingyu +5 more
doaj +1 more source
Quality-Oriented Hybrid Path Planning Based on A* and Q-Learning for Unmanned Aerial Vehicle
IEEE Access, 2022 Unmanned aerial vehicles (UAVs) are playing an increasingly important role in people’s daily lives due to their low cost of operation, low requirements for ground support, high maneuverability, high environmental adaptability, and high safety. Yet
Dongcheng Li +4 more
doaj +1 more source
FUEL: Fast UAV Exploration Using Incremental Frontier Structure and Hierarchical Planning [PDF]
IEEE Robotics and Automation Letters, 2020 Autonomous exploration is a fundamental problem for various applications of unmanned aerial vehicles(UAVs). Existing methods, however, were demonstrated to insufficient exploration rate, due to the lack of efficient global coverage, conservative motion ...
Boyu Zhou +3 more
semanticscholar +1 more source
Hierarchical Planning for Long-Horizon Manipulation with Geometric and Symbolic Scene Graphs [PDF]
IEEE International Conference on Robotics and Automation, 2020 We present a visually grounded hierarchical planning algorithm for long-horizon manipulation tasks. Our algorithm offers a joint framework of neuro-symbolic task planning and low-level motion generation conditioned on the specified goal.
Yifeng Zhu +3 more
semanticscholar +1 more source
A Hierarchical Goal-Biased Curriculum for Training Reinforcement Learning
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 Hierarchy and curricula are two techniques commonly used to improve training for Reinforcement Learning (RL) agents. Yet few works have examined how to leverage hierarchical planning to generate a curriculum for training RL Options.
Sunandita Patra +6 more
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Leveraging Demonstrations for Learning the Structure and Parameters of Hierarchical Task Networks
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023 Hierarchical Task Networks (HTNs) are a common formalism for automated planning, allowing to leverage the hierarchical structure of many activities. While HTNs have been used in many practical applications, building a complete and efficient HTN model ...
Philippe Hérail, Arthur Bit-Monnot
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Hierarchical planning for resource allocation in emergency response systems [PDF]
International Conference on Cyber-Physical Systems, 2020 A classical problem in city-scale cyber-physical systems (CPS) is resource allocation under uncertainty. Typically, such problems are modeled as Markov (or semi-Markov) decision processes.
Geoffrey Pettet +3 more
semanticscholar +1 more source