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We conducted experiments showing that agent positioning are acquired efficiently through intuitive human operation and function approximation models using ...
A hybrid computational geometry and evolutionary computation approach for generating motion trajectories to avoid a mobile obstacle in digital soccer ...
Training of Agent Positioning Using Human's Instruction. - dblp
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Bibliographic details on Training of Agent Positioning Using Human's Instruction.
<jats:p>In the real-world multiagent/multirobot problems, a position of each agent is an important factor to affect agents' performance.
May 19, 2020 · Here, we propose a conceptually simple method for training instruction-following agents with deep RL that are robust to natural human ...
May 19, 2020 · Here, we propose a conceptually simple method for training instruction-following agents with deep RL that are robust to natural human.
In this paper, we propose teaching the world model in MBRL as an effective form of Learning from. Demonstration (LfD). We demonstrate the effectiveness of this ...
Missing: Instruction. | Show results with:Instruction.
Abstract. Agents learning how to act in new environments can benefit from input from more experienced agents or humans. This paper studies interactive.
Missing: Positioning | Show results with:Positioning
Jul 3, 2017 · Learning from rewards generated by a human trainer observing an agent in action has been proven to be a powerful method for teaching ...
To effectively design agents that leverage available human expertise, we need to understand how people naturally teach. In this paper, we describe two ...