• 09:00

    WELCOME NOTE & OPENING REMARKS

  • REINFORCEMENT LEARNING ADVANCEMENTS

  • 09:15

    Deep Reinforcement Learning in the Real World

  • 09:35

    Exploring the Fundamentals of Reinforcement Learning

  • 09:55

    Transparency in Deep Reinforcement Learning Networks

  • 10:15

    COFFEE & NETWORKING BREAK

  • IMPROVING REINFORCEMENT LEARNING

  • 10:50

    Exploration vs Exploitation Dilemma

  • 11:10

    Bridging the Gap Between Value & Policy Based Reinforcement Learning

  • 11:30

    Human and Multi-Agents Systems

  • 11:50

    FIRESIDE CHAT: Human-Robot Interaction

  • 12:30

    LUNCH

  • REINFORCEMENT LEARNING APPLICATIONS

  • 13:30

    Transfer Deep Reinforcement Learning in 3D Environments

  • 13:50

    Improving Equality and Productivity with AI-Driven Tax Policies

  • 14:10

    Reinforcement Learning in Interactive Fiction Games

  • 14:30

    Deep Reinforcement Learning in Medicine

  • 14:50

    COFFEE & NETWORKING BREAK

  • REINFORCEMENT LEARNING FOR ROBOTICS

  • 15:15

    Secure Deep Reinforcement Learning

  • 15:35

    Learning to Act by Learning to Describe

  • 15:55

    Rewards, Resets, Exploration: Scaling Deep RL in Robotics

  • 16:15

    PANEL: What Are the Key Obstacles Preventing the Progression and Application of Deep RL in Industry?

  • 17:00

    NETWORKING DRINKS RECEPTION

  • 18:00

    END OF DAY 1

  • THIS SCHEDULE TAKES PLACE ON DAY 1

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