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Showing 1 to 6 of 6 for “"learning to collaborate"”.

  1. Learning to collaborate : robots building together

    … settings. The standard industry approach to robotic assembly lines utilizes fixed robotic arms and prioritizes speed and precision over customization. With a recent shift towards mobile multi-robot teams, researchers have developed a variety of approaches ranging from planning with …

    mit Repository record for Learning to collaborate : robots building together (opens in a new tab)

  2. Learning to collaborate : lessons from the design studio

    … and the Role of the Critic), as they apply to both the process and products of collaborative design. The theoretical discussion is supported with data collected from observations of two 'collaborative' studios organized by the School of Architecture and Planning at MIT. Effective …

    mit Repository record for Learning to collaborate : lessons from the design studio (opens in a new tab)

  3. ENDLESS SCROLLING: TECHNOLOGY, (DIS)CONNECTION, AND PLACE IN TIMES OF COVID-19

    … people connected with one another in their day to day lives. Though experiences differed, many turned to communication technology as a means to continue to connect despite COVID restrictions. For some this meant learning to collaborate with coworkers through a screen, while for others it allowed …

    kennesaw Repository record for ENDLESS SCROLLING: TECHNOLOGY, (DIS)CONNECTION, AND PLACE IN TIMES OF COVID-19 (opens in a new tab)

  4. Communication and generalization in multi-agent learning

    Multi-agent learning aims to allow artificial intelligence (AI) agents to learn from interactions with other agents in an environment. However, as AI increasingly integrates into real-world systems, significant challenges arise in how to robustly interact with and communicate with a variety of …

    texas Repository record for Communication and generalization in multi-agent learning (opens in a new tab)

  5. Model-free reinforcement learning in non-stationary Markov Decision Processes

    Reinforcement learning (RL) studies the problem where an agent maximizes its cumulative reward through sequential interactions with an initially unknown environment, usually modeled by a Markov Decision Process (MDP). The classical RL literature typically assumes that the state transition functions …

    uiuc Repository record for Model-free reinforcement learning in non-stationary Markov Decision Processes (opens in a new tab)

  6. Improving computer-mediated collaboration: development and empirical evaluation of two instructional support methods

    … is a precondition for success in many new learning and working contexts, but it is hard to achieve. Two instructional approaches were developed to improve collaboration in such settings by promoting people’s capabilities to collaborate in a fruitful way and furthering their understanding of …

    freiburg-diss Repository record for Improving computer-mediated collaboration: development and empirical evaluation of two instructional support methods (opens in a new tab)