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
2008
Approximate algorithms for credal networks with binary variables
Ide J, Cozman F. Approximate algorithms for credal networks with binary variables. International Journal Of Approximate Reasoning 2008, 48: 275-296. DOI: 10.1016/j.ijar.2007.09.003.Peer-Reviewed Original ResearchCredal networksApproximate inferenceBinary variablesApproximate algorithmLoopy belief propagationFamily of algorithmsOnly binary variablesExact inferenceVariational techniquePolynomial complexityBelief propagationBayesian networkSuch networksBelief functionsInferencePossibilistic measuresAlgorithmVague beliefPolytreesNetworkVariablesPropagationComplexity