We explored the reliability of detecting a learner's affect from conversational features extracted from interactions with AutoTutor, an intelligent tutoring system that helps...
Sidney K. D'Mello, Scotty D. Craig, Amy M. Withers...
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
We present a framework for the formal verification of abstract state machine (ASM) designs using the multiway decision graphs (MDG) tool. ASM is a state based language for describ...
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
In this paper, we propose a new formalism, named the Timed Communicating Finite State Machine (Timed CFSM), for specifying and verifying time-critical systems. Timed CFSM preserve...