Zobrazeno 1 - 10
of 253
pro vyhledávání: '"Laird, John E."'
Cognitive systems generally require a human to translate a problem definition into some specification that the cognitive system can use to attempt to solve the problem or perform the task. In this paper, we illustrate that large language models (LLMs
Externí odkaz:
http://arxiv.org/abs/2405.12147
Large language models (LLMs) provide capabilities far beyond sentence completion, including question answering, summarization, and natural-language inference. While many of these capabilities have potential application to cognitive systems, our resea
Externí odkaz:
http://arxiv.org/abs/2310.06846
Large language models (LLMs) offer significant promise as a knowledge source for task learning. Prompt engineering has been shown to be effective for eliciting knowledge from an LLM, but alone it is insufficient for acquiring relevant, situationally
Externí odkaz:
http://arxiv.org/abs/2306.06770
Human behavior is conditioned by codes and norms that constrain action. Rules, ``manners,'' laws, and moral imperatives are examples of classes of constraints that govern human behavior. These systems of constraints are "messy:" individual constraint
Externí odkaz:
http://arxiv.org/abs/2303.04352
Language models (LLMs) offer potential as a source of knowledge for agents that need to acquire new task competencies within a performance environment. We describe efforts toward a novel agent capability that can construct cues (or "prompts") that re
Externí odkaz:
http://arxiv.org/abs/2209.07636
Autonomous agents are able to draw on a wide variety of potential sources of task knowledge; however current approaches invariably focus on only one or two. Here we investigate the challenges and impact of exploiting diverse knowledge sources to lear
Externí odkaz:
http://arxiv.org/abs/2208.09554
Autor:
Laird, John E.
This paper is the recommended initial reading for a functional overview of Soar, version 9.6. It includes an abstract overview of the architectural structure of Soar including its processing, memories, learning modules, their interfaces, and the repr
Externí odkaz:
http://arxiv.org/abs/2205.03854
Autor:
Laird, John E.
This is a detailed analysis and comparison of the ACT-R and Soar cognitive architectures, including their overall structure, their representations of agent data and metadata, and their associated processing. It focuses on working memory, procedural m
Externí odkaz:
http://arxiv.org/abs/2201.09305
Language models (LMs) are sentence-completion engines trained on massive corpora. LMs have emerged as a significant breakthrough in natural-language processing, providing capabilities that go far beyond sentence completion including question answerin
Externí odkaz:
http://arxiv.org/abs/2109.08270
Autor:
Stocco, Andrea, Sibert, Catherine, Steine-Hanson, Zoe, Koh, Natalie, Laird, John E., Lebiere, Christian J., Rosenbloom, Paul
Publikováno v:
In NeuroImage 15 July 2021 235
