Search Results for author: Antonello Ceravola

Found 4 papers, 0 papers with code

CoPAL: Corrective Planning of Robot Actions with Large Language Models

no code implementations11 Oct 2023 Frank Joublin, Antonello Ceravola, Pavel Smirnov, Felix Ocker, Joerg Deigmoeller, Anna Belardinelli, Chao Wang, Stephan Hasler, Daniel Tanneberg, Michael Gienger

In the pursuit of fully autonomous robotic systems capable of taking over tasks traditionally performed by humans, the complexity of open-world environments poses a considerable challenge.

Motion Planning Task and Motion Planning

Analysis of ChatGPT on Source Code

no code implementations1 Jun 2023 Ahmed R. Sadik, Antonello Ceravola, Frank Joublin, Jibesh Patra

This paper explores the use of Large Language Models (LLMs) and in particular ChatGPT in programming, source code analysis, and code generation.

Code Generation

A Glimpse in ChatGPT Capabilities and its impact for AI research

no code implementations10 May 2023 Frank Joublin, Antonello Ceravola, Joerg Deigmoeller, Michael Gienger, Mathias Franzius, Julian Eggert

Large language models (LLMs) have recently become a popular topic in the field of Artificial Intelligence (AI) research, with companies such as Google, Amazon, Facebook, Amazon, Tesla, and Apple (GAFA) investing heavily in their development.

Question Answering Text Generation

Designing Interaction for Multi-agent Cooperative System in an Office Environment

no code implementations15 Feb 2020 Chao Wang, Stephan Hasler, Manuel Muehlig, Frank Joublin, Antonello Ceravola, Joerg Deigmoeller, Lydia Fischer

Future intelligent system will involve very various types of artificial agents, such as mobile robots, smart home infrastructure or personal devices, which share data and collaborate with each other to execute certain tasks. Designing an efficient human-machine interface, which can support users to express needs to the system, supervise the collaboration progress of different entities and evaluate the result, will be challengeable.

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