2022
Hierarchical Reinforcement Learning for Air Combat at DARPA's AlphaDogfight Trials
Pope A, Ide J, Miovi D, Diaz H, Twedt J, Alcedo K, Walker T, Rosenbluth D, Ritholtz L, Javorsek D. Hierarchical Reinforcement Learning for Air Combat at DARPA's AlphaDogfight Trials. IEEE Transactions On Artificial Intelligence 2022, 4: 1371-1385. DOI: 10.1109/tai.2022.3222143.Peer-Reviewed Original ResearchAir combatLow-level policiesHierarchical reinforcement learningField of roboticsAdoption of AIHierarchical Deep ReinforcementContinuous control problemsDeep reinforcementArtificial intelligenceReward shapingContinuous state spaceReinforcement learningState spaceAutonomous controlExpert knowledgeCombat systemExpert pilotsAIImportant challengeControl problemRoboticsIntelligenceLearningComplexitySpace
2013
Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease
Gorzelic P, Schiff S, Sinha A. Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease. Journal Of Neural Engineering 2013, 10: 026016. PMID: 23449002, DOI: 10.1088/1741-2560/10/2/026016.Peer-Reviewed Original ResearchConceptsFeedback controller designController designPID controlHigh-level control strategyBetter controller performanceFeedback control methodFeedback control problemController performanceDerivative controlControl methodFeedback controllerControl inputControl lawControl strategyProportional controlOnline estimatesComputational modelControl problemConsiderable further reductionDerivative methodologyOptimal controlAdaptive methodRelay capabilityStimulation algorithmDesign
2003
Seizure Control using Feedback and Electric Fields
Gluckman B, Schiff S. Seizure Control using Feedback and Electric Fields. Biological And Medical Physics, Biomedical Engineering 2003, 263-282. DOI: 10.1007/978-3-662-05048-4_15.Peer-Reviewed Original Research
1999
A New Approach to 3D Sulcal Ribbon Finding from MR Images
Zeng X, Staib L, Schultz R, Tagare H, Win L, Duncan J. A New Approach to 3D Sulcal Ribbon Finding from MR Images. Lecture Notes In Computer Science 1999, 1679: 148-157. DOI: 10.1007/10704282_16.Peer-Reviewed Original ResearchGeneral segmentation methodsMR brain imagesDistance functionLittle manual interventionDeformable surface modelSegmentation workSegmentation methodManual interventionNew approachBrain imagesContour modelCortex segmentationDynamic programmingLevel setsNatural followImagesMR imagesControl problemSurface modelSegmentationQuantitative resultsProgramming
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply