Results 301 to 310 of about 9,013,912 (355)

Model-Based Reasoning

The Handbook of Applied Expert Systems, 2019
R. Fjellheim
semanticscholar   +2 more sources

A Case-Based Reasoning Model for Depression Based on Three-Electrode EEG Data

IEEE Transactions on Affective Computing, 2020
Depression, threatening the well-being of millions, has become one of the major diseases in the past decade. However, the current method of diagnosing depression is questionnaire-based interviews, which is labor-intensive and highly dependent on doctors’
Hanshu Cai, Xiangzi Zhang, Yanhao Zhang, Ziyang Wang, Bin Hu   +4 more
semanticscholar   +1 more source

Developing Model‐Based Reasoning

Interactive Learning Environments, 1994
Key elements of the structure and function of models in mathematics and science are identified. These elements are used as a basis for discussing the development of model‐based reasoning. A microgenetic study examines the beginnings of model‐based reasoning in a pair of fourth‐ and fifth‐grade children who solved several problems about chance and ...
Richard Lehrer, Jeffrey Horvath, Leona Schauble   +2 more
openaire   +1 more source

Model Based Temporal Reasoning

SPIE Proceedings, 1988
Systems that assess the real world must cope with evidence that is uncertain, ambiguous, and spread over time. Typically, the most important function of an assessment system is to identify when activities are occurring that are unusual or unanticipated. Model based temporal reasoning addresses both of these requirements.
Marla J. Rabin, Paul R. Spinrad, Thomas C. Fall   +2 more
openaire   +1 more source

Applications of qualitative model-based reasoning

Control Engineering Practice, 1993
Abstract This paper provides an introduction to the concepts behind both model-based reasoning and qualitative reasoning. The aim is to show how qualitative methods can be used to build powerful model-based reasoning systems. Different classes of models are discussed and a number of approaches to qualitative reasoning are introduced.
J.E. Hunt, M.H. Lee, C.J. Price
openaire   +1 more source

Large Language Model based Multi-Agents: A Survey of Progress and Challenges

International Joint Conference on Artificial Intelligence
Large Language Models (LLMs) have achieved remarkable success across a wide array of tasks. Due to their notable capabilities in planning and reasoning, LLMs have been utilized as autonomous agents for the automatic execution of various tasks.
Taicheng Guo, Xiuying Chen, Yaqi Wang, Ruidi Chang, Shichao Pei, N. Chawla, Olaf Wiest, Xiangliang Zhang   +7 more
semanticscholar   +1 more source

CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering

International Conference on Case-Based Reasoning
Retrieval-Augmented Generation (RAG) enhances Large Language Model (LLM) output by providing prior knowledge as context to input. This is beneficial for knowledge-intensive and expert reliant tasks, including legal question-answering, which require ...
N. Wiratunga, Ramitha Abeyratne, Lasal Jayawardena, Kyle Martin, Stewart Massie, Ikechukwu Nkisi-Orji, R. Weerasinghe, A. Liret, Bruno Fleisch   +8 more
semanticscholar   +1 more source

Model-Based Reasoning in Mathematical Practice

2017
The nature of mathematical reasoning has been the scope of many discussions in philosophy of mathematics. This chapter addresses how mathematicians engage in specific modeling practices. We show, by making only minor alterations to accounts of scientific modeling, that these are also suitable for analyzing mathematical reasoning.
Van Kerkhove, Bart, Frans, Joachim, Goyvaerts, Isar   +2 more
openaire   +2 more sources

Learning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizing

Conference on Empirical Methods in Natural Language Processing
Large Language Models (LLMs) have demonstrated significant potential in handling complex reasoning tasks through step-by-step rationale generation. However, recent studies have raised concerns regarding the hallucination and flaws in their reasoning ...
Fangkai Jiao, Chengwei Qin, Zhengyuan Liu, Nancy F. Chen, Shafiq R. Joty   +4 more
semanticscholar   +1 more source

Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning

arXiv.org
Inspired by the success of DeepSeek-R1, we explore the potential of rule-based reinforcement learning (RL) in large reasoning models. To analyze reasoning dynamics, we use synthetic logic puzzles as training data due to their controllable complexity and ...
Tian Xie, Zitian Gao, Qingnan Ren, Haoming Luo, Yuqian Hong, Bryan Dai, Joey Zhou, Kai Qiu, Zhirong Wu, Chong Luo   +9 more
semanticscholar   +1 more source