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From Biological Synapses to “Intelligent” Robots
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In: ISSN: 2079-9292 ; Electronics ; https://hal.archives-ouvertes.fr/hal-03590998 ; Electronics, MDPI, 2022, 11 (5), pp.707. ⟨10.3390/electronics11050707⟩ (2022)
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Cross-Situational Learning Towards Robot Grounding
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In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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Cross-Situational Learning Towards Robot Grounding
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In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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Finding the best way to put media bias research into practice via an annotation app ...
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Are neural language models sensitive to false belief? A computational study. ...
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Structured, flexible, and robust: comparing linguistic plans and explanations generated by humans and large language models ...
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Can distributional semantics explain performance on the false belief task? ...
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Learning Bidirectional Translation between Descriptions and Actions with Small Paired Data ...
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SGL: Symbolic Goal Learning in a Hybrid, Modular Framework for Human Instruction Following ...
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Self-supervised 3D Semantic Representation Learning for Vision-and-Language Navigation ...
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Interactive Robotic Grasping with Attribute-Guided Disambiguation ...
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The Enforcers: Consistent Sparse-Discrete Methods for Constraining Informative Emergent Communication ...
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Abstract:
Communication enables agents to cooperate to achieve their goals. Learning when to communicate, i.e. sparse communication, is particularly important where bandwidth is limited, in situations where agents interact with humans, in partially observable scenarios where agents must convey information unavailable to others, and in non-cooperative scenarios where agents may hide information to gain a competitive advantage. Recent work in learning sparse communication, however, suffers from high variance training where, the price of decreasing communication is a decrease in reward, particularly in cooperative tasks. Sparse communications are necessary to match agent communication to limited human bandwidth. Humans additionally communicate via discrete linguistic tokens, previously shown to decrease task performance when compared to continuous communication vectors. This research addresses the above issues by limiting the loss in reward of decreasing communication and eliminating the penalty for discretization. In ... : Submitted to IJCAI 2022 ...
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Keyword:
FOS Computer and information sciences; Machine Learning cs.LG; Multiagent Systems cs.MA; Robotics cs.RO
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URL: https://dx.doi.org/10.48550/arxiv.2201.07452 https://arxiv.org/abs/2201.07452
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The Construction of the Robot in Language and Culture, “Intercultural Robotics” and the “Third Robot Culture” ...
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Cheng, Lin. - : Technology and Language, 3(1), 1-8, 2022
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The influence of animacy on perspective-taking and word order during language production ...
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Unsupervised Multimodal Word Discovery based on Double Articulation Analysis with Co-occurrence cues ...
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Machine infelicity in a poignant visitor setting: Comparing human and AI’s ability to analyze discourse
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In: Research outputs 2014 to 2021 (2022)
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Integrating Blockchains and Intelligent Agents in the Pursuit of Artificial General Intelligence
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In: Senior Honors Theses (2022)
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