Decision Making
2039 papers with code • 1 benchmarks • 38 datasets
Decision Making is a complex task that involves analyzing data (of different level of abstraction) from disparate sources and with different levels of certainty, merging the information by weighing in on some data source more than other, and arriving at a conclusion by exploring all possible alternatives.
Source: Complex Events Recognition under Uncertainty in a Sensor Network
Benchmarks
These leaderboards are used to track progress in Decision Making
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Libraries
Use these libraries to find Decision Making models and implementations
D4RL
Charades-STA
FairFace
VizDoom
TORCS
LogiQA
ShARC
GazeFollow
Latest papers with no code
Designing forecasting software for forecast users: Empowering non-experts to create and understand their own forecasts
In practice, forecasts are often used by domain experts and managers with little forecasting expertise.
Mapping Wireless Networks into Digital Reality through Joint Vertical and Horizontal Learning
In recent years, the complexity of 5G and beyond wireless networks has escalated, prompting a need for innovative frameworks to facilitate flexible management and efficient deployment.
Adaptive Collaboration Strategy for LLMs in Medical Decision Making
Our novel framework, Medical Decision-making Agents (MDAgents) aims to address this gap by automatically assigning the effective collaboration structure for LLMs.
A Survey of Decomposition-Based Evolutionary Multi-Objective Optimization: Part I-Past and Future
In the first part, we present a comprehensive survey of the development of MOEA/D from its origin to the current state-of-the-art approaches.
A Practical Multilevel Governance Framework for Autonomous and Intelligent Systems
This work presents a practical framework for multilevel governance of AIS.
In-situ process monitoring and adaptive quality enhancement in laser additive manufacturing: a critical review
Future directions are proposed, with an emphasis on multimodal sensor fusion for multiscale defect prediction and fault diagnosis, ultimately enabling self-adaptation in LAM processes.
Multifidelity Surrogate Models: A New Data Fusion Perspective
Multifidelity surrogate modelling combines data of varying accuracy and cost from different sources.
Beyond Collaborative Filtering: A Relook at Task Formulation in Recommender Systems
That is, we often conceptualize RecSys as the task of predicting missing values in a static user-item interaction matrix, rather than predicting a user's decision on the next interaction within a dynamic, changing, and application-specific context.
Explainable Deepfake Video Detection using Convolutional Neural Network and CapsuleNet
Deepfake technology, derived from deep learning, seamlessly inserts individuals into digital media, irrespective of their actual participation.
Explainable AI for Fair Sepsis Mortality Predictive Model
By focusing on the predictive modeling of sepsis-related mortality, we propose a method that learns a performance-optimized predictive model and then employs the transfer learning process to produce a model with better fairness.
