A5075375795- Human Mobility and Location-Based Analysis
- Traffic Prediction and Management Techniques
- Data Management and Algorithms
- Autonomous Vehicle Technology and Safety
- Data-Driven Disease Surveillance
- Artificial Intelligence in Law
- Complex Network Analysis Techniques
- Recommender Systems and Techniques
- Personal Information Management and User Behavior
- Multi-Agent Systems and Negotiation
York University
2023-2025
Sharif University of Technology
2022
In this paper, we present a novel framework for enhancing the capabilities of large language models (LLMs) by leveraging power multi-agent systems. Our introduces collaborative environment where multiple intelligent agent components, each with distinctive attributes and roles, work together to handle complex tasks more efficiently effectively. We demonstrate practicality versatility our through case studies in artificial general intelligence (AGI), specifically focusing on Auto-GPT BabyAGI...
Trajectory prediction aims to estimate an entity’s future path using its current position and historical movement data, benefiting fields like autonomous navigation, robotics, human analytics. Deep learning approaches have become key in this area, utilizing large-scale trajectory datasets model patterns, but face challenges managing complex spatial dependencies adapting dynamic environments. To address these challenges, we introduce TrajLearn , a novel for that leverages generative modeling...
Social media platforms thrive upon the intertwined combination of user-created content and social interaction between these users.
Research on trajectory data mining relies appropriate datasets, including Gps-based geolocations, check-in to points of interest (Pois), and synthetic datasets. Even though some are accessible, the majority mobility datasets typically discovered through ad-hoc searches lack comprehensive documentation their generation process or source reproduce curated customized versions them. At same time, there has been a growing in new type data, describing trajectories as sequences higher-order...
Trajectory prediction aims to estimate an entity's future path using its current position and historical movement data, benefiting fields like autonomous navigation, robotics, human analytics. Deep learning approaches have become key in this area, utilizing large-scale trajectory datasets model patterns, but face challenges managing complex spatial dependencies adapting dynamic environments. To address these challenges, we introduce TrajLearn, a novel for that leverages generative modeling...