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Showing 1 to 4 of 4 for “"Multi-Agent Domains"”.

  1. Intent Recognition in Multi-Agent Domains

    … interaction, but is also useful in adversarial domains, as discussed in this thesis. It is especially important to be capable of performing intent recognition in multi-agent settings, both in terms of recognizing low-level intentions for individual agents, and of recognizing coordinated agents …

    unr Repository record for Intent Recognition in Multi-Agent Domains (opens in a new tab)

  2. Several Reinforcement Learning Methods in Mean-Field Games with Binary Action Spaces

    … in which interactions between intelligent agents and the environment enable agents to learn and solve sequential decision-making problems through accumulating rewards with delays. Despite much success in single-player settings, reinforcement learning in multi-agent domains remains a …

    carleton Repository record for Several Reinforcement Learning Methods in Mean-Field Games with Binary Action Spaces (opens in a new tab)

  3. Building Strategic AI Agents for Human-centric Multi-agent Systems

    … the challenge of developing strategic AI agents capable of effective decision-making and communication in human-centric multi-agent systems. While significant progress has been made in AI for strategic decision-making, creating agents that can seamlessly interact with humans in …

    mit Repository record for Building Strategic AI Agents for Human-centric Multi-agent Systems (opens in a new tab)

  4. Team Learning from Human Demonstration with Coordination Confidence

    … of success. A related technique, called Human Agent Transfer (HAT), and its confidence-based derivatives have been successfully applied to single agent RL. This paper investigates their application to collaborative multi- agent RL problems. We show that a first-cut extension may leave room for …

    usm Repository record for Team Learning from Human Demonstration with Coordination Confidence (opens in a new tab)