This paper presents the dynamics of multiple reinforcement learning agents from an Evolutionary Game Theoretic (EGT) perspective. We provide a Replicator Dynamics model for tradit...
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
This paper presents a self-organizing cognitive architecture, known as TD-FALCON, that learns to function through its interaction with the environment. TD-FALCON learns the value ...
When the transition probabilities and rewards of a Markov Decision Process are specified exactly, the problem can be solved without any interaction with the environment. When no s...
The resource constraint project scheduling problem (RCPSP) is an NP-hard benchmark problem in scheduling which takes into account the limitation of resources’ availabilities in ...