Search Results for author: Shivam Goel

Found 4 papers, 2 papers with code

NovelGym: A Flexible Ecosystem for Hybrid Planning and Learning Agents Designed for Open Worlds

no code implementations7 Jan 2024 Shivam Goel, Yichen Wei, Panagiotis Lymperopoulos, Matthias Scheutz, Jivko Sinapov

To this end, we introduce NovelGym, a flexible and adaptable ecosystem designed to simulate gridworld environments, serving as a robust platform for benchmarking reinforcement learning (RL) and hybrid planning and learning agents in open-world contexts.

Autonomous Vehicles Benchmarking +1

A Framework for Few-Shot Policy Transfer through Observation Mapping and Behavior Cloning

1 code implementation13 Oct 2023 Yash Shukla, Bharat Kesari, Shivam Goel, Robert Wright, Jivko Sinapov

We use Generative Adversarial Networks (GANs) along with a cycle-consistency loss to map the observations between the source and target domains and later use this learned mapping to clone the successful source task behavior policy to the target domain.

Transfer Learning

RAPid-Learn: A Framework for Learning to Recover for Handling Novelties in Open-World Environments

1 code implementation24 Jun 2022 Shivam Goel, Yash Shukla, Vasanth Sarathy, Matthias Scheutz, Jivko Sinapov

We propose RAPid-Learn: Learning to Recover and Plan Again, a hybrid planning and learning method, to tackle the problem of adapting to sudden and unexpected changes in an agent's environment (i. e., novelties).

Transfer Learning

SPOTTER: Extending Symbolic Planning Operators through Targeted Reinforcement Learning

no code implementations24 Dec 2020 Vasanth Sarathy, Daniel Kasenberg, Shivam Goel, Jivko Sinapov, Matthias Scheutz

Symbolic planning models allow decision-making agents to sequence actions in arbitrary ways to achieve a variety of goals in dynamic domains.

Decision Making reinforcement-learning +1

Cannot find the paper you are looking for? You can Submit a new open access paper.