OPEB: Open Physical Environment Benchmark for Artificial Intelligence
Abstract
Artificial Intelligence methods to solve continuous- control tasks have made significant progress in recent years. However, these algorithms have important limitations and still need significant improvement to be used in industry and real- world applications. This means that this area is still in an active research phase. To involve a large number of research groups, standard benchmarks are needed to evaluate and compare proposed algorithms. In this paper, we propose a physical environment benchmark framework to facilitate collaborative research in this area by enabling different research groups to integrate their designed benchmarks in a unified cloud-based repository and also share their actual implemented benchmarks via the cloud. We demonstrate the proposed framework using an actual implementation of the classical mountain-car example and present the results obtained using a Reinforcement Learning algorithm.
- Publication:
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arXiv e-prints
- Pub Date:
- July 2017
- DOI:
- 10.48550/arXiv.1707.00790
- arXiv:
- arXiv:1707.00790
- Bibcode:
- 2017arXiv170700790M
- Keywords:
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- Computer Science - Artificial Intelligence
- E-Print:
- Accepted in 3rd IEEE International Forum on Research and Technologies for Society and Industry 2017