53 citations · 232 across the 44 of their papers we have counts for
4 papers · 1 filter
Learning and Using Abstractions for Robot Planning
Naman Shah, Abhyudaya Srinet, Siddharth Srivastava
Robot motion planning involves computing a sequence of valid robot configurations that take the robot from its initial state to a goal state. Solving a motion planning problem opti…
Learning Generalized Relational Heuristic Networks for Model-Agnostic Planning
Rushang Karia, Siddharth Srivastava
Computing goal-directed behavior is essential to designing efficient AI systems. Due to the computational complexity of planning, current approaches rely primarily upon hand-coded…
Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Inscrutable Representations
Sarath Sreedharan, Utkarsh Soni, Mudit Verma +2
As increasingly complex AI systems are introduced into our daily lives, it becomes important for such systems to be capable of explaining the rationale for their decisions and allo…
Generative and discriminative training of Boltzmann machine through Quantum annealing
Siddhartha Srivastava, Veera Sundararaghavan
A hybrid quantum-classical method for learning Boltzmann machines (BM) for a generative and discriminative task is presented. Boltzmann machines are undirected graphs with a networ…