Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch
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Updated
Apr 1, 2019 - Python
Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch
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RL environment replicating the werewolf game to study emergent communication
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simple ABM program to simulate a moving danger (e.g., fire) and people in a confined space trying to escape the danger
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Tool to measure tree-structuredness of the internal algorithm learnt by a transformer
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Project describing how social complexity relates to communication complexity
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Two different types of creatures fight in a 15 * 15 map where one type can infect the other and make the other become one of theirs.
A simulation tool for exploring weird emergent behaviour in particle systems.
Text adventure and MUD engine with AI NPCs, Discord integration, and Stable Diffusion visuals
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