Search Results for author: Shashank Rao Marpally

Found 3 papers, 2 papers with code

Discovering User-Interpretable Capabilities of Black-Box Planning Agents

1 code implementation28 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.

Decision Making

Asking the Right Questions: Learning Interpretable Action Models Through Query Answering

1 code implementation29 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.

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