Flexible multi-objective particle swarm optimization clustering with game theory to address human activity discovery fully unsupervised.
Parham HadikhaniDaphne Teck Ching LaiWee-Hong OngPublished in: Image Vis. Comput. (2024)
Keyphrases
- game theory
- human activities
- fully unsupervised
- multi objective particle swarm optimization
- game theoretic
- activity recognition
- nash equilibrium
- cooperative
- multi agent systems
- statistical physics
- sensor data
- resource allocation
- fictitious play
- nash equilibria
- human computer interaction
- action recognition
- multi agent learning
- multi objective
- data points
- data streams
- upper bound
- lower bound
- search algorithm