Cohort Intelligence: A Self Supervised Learning Behavior von Kulkarni, Anand J., Durugkar, Ishan P., Kumar, Mrinal

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Towards a Real-Time, Low-Resource, End-to-End Object Detection Pipeline for Robot Soccer von Narayanaswami, Sai Kiran, Tec, Mauricio, Durugkar, Ishan, Desai, Siddharth, Masetty, Bharath, Narvekar, Sanmit, Stone, Peter

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N-Agent Ad Hoc Teamwork von Wang, Caroline, Rahman, Arrasy, Durugkar, Ishan, Liebman, Elad, Stone, Peter

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f$-Policy Gradients: A General Framework for Goal Conditioned RL using $f$-Divergences von Agarwal, Siddhant, Durugkar, Ishan, Stone, Peter, Zhang, Amy

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ABC: Adversarial Behavioral Cloning for Offline Mode-Seeking Imitation Learning von Hudson, Eddy, Durugkar, Ishan, Warnell, Garrett, Stone, Peter

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DM$^2$: Decentralized Multi-Agent Reinforcement Learning for Distribution Matching von Wang, Caroline, Durugkar, Ishan, Liebman, Elad, Stone, Peter

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Wasserstein Distance Maximizing Intrinsic Control von Durugkar, Ishan, Hansen, Steven, Spencer, Stephen, Mnih, Volodymyr

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Adversarial Intrinsic Motivation for Reinforcement Learning von Durugkar, Ishan, Tec, Mauricio, Niekum, Scott, Stone, Peter

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N-Agent Ad Hoc Teamwork von Wang, Caroline, Rahman, Arrasy, Durugkar, Ishan, Liebman, Elad, Stone, Peter

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Reducing Sampling Error in Batch Temporal Difference Learning von Pavse, Brahma, Durugkar, Ishan, Hanna, Josiah, Stone, Peter

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(f\)-Policy Gradients: A General Framework for Goal Conditioned RL using \(f\)-Divergences von Agarwal, Siddhant, Durugkar, Ishan, Stone, Peter, Zhang, Amy

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Multi-Preference Actor Critic von Durugkar, Ishan, Hausknecht, Matthew, Swaminathan, Adith, MacAlpine, Patrick

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DM\(^2\): Decentralized Multi-Agent Reinforcement Learning for Distribution Matching von Wang, Caroline, Durugkar, Ishan, Liebman, Elad, Stone, Peter

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An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch von Desai, Siddharth, Durugkar, Ishan, Karnan, Haresh, Warnell, Garrett, Hanna, Josiah, Stone, Peter

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ABC: Adversarial Behavioral Cloning for Offline Mode-Seeking Imitation Learning von Hudson, Eddy, Durugkar, Ishan, Warnell, Garrett, Stone, Peter

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Generative Multi-Adversarial Networks von Durugkar, Ishan, Gemp, Ian, Mahadevan, Sridhar

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Adversarial Intrinsic Motivation for Reinforcement Learning von Durugkar, Ishan, Tec, Mauricio, Niekum, Scott, Stone, Peter

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Wasserstein Distance Maximizing Intrinsic Control von Durugkar, Ishan, Hansen, Steven, Spencer, Stephen, Mnih, Volodymyr

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Reducing Sampling Error in Batch Temporal Difference Learning von Brahma Pavse, Durugkar, Ishan, Hanna, Josiah, Stone, Peter

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Deep Reinforcement Learning With Macro-Actions von Durugkar, Ishan P, Rosenbaum, Clemens, Dernbach, Stefan, Mahadevan, Sridhar

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