1 code implementation • 28 Jul 2021 • Pulkit Verma, Shashank Rao Marpally, Siddharth Srivastava
Starting from a set of user-interpretable state properties, an AI agent, and a simulator that the agent can interact with, our algorithm returns a set of high-level capabilities with their parameterized descriptions.
no code implementations • 16 Apr 2020 • Mehrdad Zakershahrak, Shashank Rao Marpally, Akshay Sharma, Ze Gong, Yu Zhang
Given this sequential process, a formulation based on goal-based MDP for generating progressive explanations is presented.
1 code implementation • 29 Dec 2019 • Pulkit Verma, Shashank Rao Marpally, Siddharth Srivastava
This paper develops a new approach for estimating an interpretable, relational model of a black-box autonomous agent that can plan and act.