Active Inference for Autonomous Decision-Making with Contextual Multi-Armed Bandits
Shohei Wakayama,Nisar Ahmed,Shohei Wakayama,Nisar Ahmed
In autonomous robotic decision-making under uncertainty, the tradeoff between exploitation and exploration of available options must be considered. If secondary information associated with options can be utilized, such decision-making problems can often be formulated as contextual multi-armed bandits (CMABs). In this study, we apply active inference, which has been actively studied in the field of...
