Title: DMSpreading: Spreading activation default weights · Issue #25 · CarletonCognitiveModelingLab/python_actr · GitHub
Open Graph Title: DMSpreading: Spreading activation default weights · Issue #25 · CarletonCognitiveModelingLab/python_actr
X Title: DMSpreading: Spreading activation default weights · Issue #25 · CarletonCognitiveModelingLab/python_actr
Description: If I'm reading the code correctly, DMSpreading takes zero or more buffers as arguments and sets their spreading activation weights to 1.0 by default: def __init__(self,memory,*buffers): MemorySubModule.__init__(self,memory) self.strength...
Open Graph Description: If I'm reading the code correctly, DMSpreading takes zero or more buffers as arguments and sets their spreading activation weights to 1.0 by default: def __init__(self,memory,*buffers): MemorySubMo...
X Description: If I'm reading the code correctly, DMSpreading takes zero or more buffers as arguments and sets their spreading activation weights to 1.0 by default: def __init__(self,memory,*buffers): MemoryS...
Opengraph URL: https://github.com/CarletonCognitiveModelingLab/python_actr/issues/25
X: @github
Domain: patch-diff.githubusercontent.com
{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"DMSpreading: Spreading activation default weights","articleBody":"If I'm reading the code correctly, `DMSpreading` takes zero or more buffers as arguments and sets their spreading activation weights to 1.0 by default:\r\n\r\n```py\r\n def __init__(self,memory,*buffers):\r\n MemorySubModule.__init__(self,memory)\r\n self.strength=1\r\n self.buffers=buffers\r\n self.weight={}\r\n for b in buffers: \r\n self.weight[b]=1\r\n self.slots={}\r\n```\r\n\r\nThen I guess the user is supposed to reset the ones that are not supposed to be 1.0?\r\n\r\n```py\r\n spread = DMSpreading( memory, goal )\r\n spread.weight[goal] = 0.0\r\n```\r\n\r\nI believe these weights are the equivalent of ACT-R's `activation spread parameters`.\r\n\r\nHere are the activation spread parameter defaults listed in the ACT-R manual:\r\n\r\n| buffer | ACT-R param | default|\r\n|--|--|--|\r\n| Aural buffer | :aural-activation | 0.0 |\r\n| Aural-location buffer | :aural-location-activation | 0.0 |\r\n| Goal buffer | :ga | 0.0 |\r\n| Imaginal buffer | :imaginal-activation | 1.0 |\r\n| Imaginal-action buffer | :imaginal-action-activation | 0.0 |\r\n| Manual buffer | :manual-activation | 0.0 |\r\n| Production buffer | :production-activation | 0.0 |\r\n| Retrieval buffer | :retrieval-activation | 0.0 |\r\n| Temporal buffer | :temporal-activation | 0.0 |\r\n| Visual buffer | :visual-activation | 0.0 |\r\n| Visual-location buffer | :visual-location-activation | 0.0 |\r\n| Vocal buffer | :vocal-activation | 0.0 |\r\n\r\nSo it seems like the default should be 0.0?\r\n\r\n(Related to https://github.com/asmaloney/gactar/issues/325)","author":{"url":"https://github.com/asmaloney","@type":"Person","name":"asmaloney"},"datePublished":"2023-07-31T15:25:10.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":0},"url":"https://github.com/25/python_actr/issues/25"}
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| og:image:alt | If I'm reading the code correctly, DMSpreading takes zero or more buffers as arguments and sets their spreading activation weights to 1.0 by default: def __init__(self,memory,*buffers): MemorySubMo... |
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