no code implementations • 6 Apr 2024 • Biplav Srivastava, Vishal Pallagani
Foundation Models (FMs) have revolutionized many areas of computing, including Automated Planning and Scheduling (APS).
no code implementations • 4 Jan 2024 • Vishal Pallagani, Kaushik Roy, Bharath Muppasani, Francesco Fabiano, Andrea Loreggia, Keerthiram Murugesan, Biplav Srivastava, Francesca Rossi, Lior Horesh, Amit Sheth
Automated Planning and Scheduling is among the growing areas in Artificial Intelligence (AI) where mention of LLMs has gained popularity.
no code implementations • 25 Jul 2023 • Bharath Muppasani, Vishal Pallagani, Biplav Srivastava, Forest Agostinelli
The fastest solver today for RC is DeepCubeA with a custom representation, and another approach is with Scorpion planner with State-Action-Space+ (SAS+) representation.
no code implementations • 25 Jul 2023 • Bharath Muppasani, Vishal Pallagani, Biplav Srivastava, Raghava Mutharaju, Michael N. Huhns, Vignesh Narayanan
Ontologies are known for their ability to organize rich metadata, support the identification of novel insights via semantic queries, and promote reuse.
no code implementations • 14 Jul 2023 • Marianna B. Ganapini, Francesco Fabiano, Lior Horesh, Andrea Loreggia, Nicholas Mattei, Keerthiram Murugesan, Vishal Pallagani, Francesca Rossi, Biplav Srivastava, Brent Venable
Values that are relevant to a specific decision scenario are used to decide when and how to use each of these nudging modalities.
no code implementations • 8 Jul 2023 • Kausik Lakkaraju, Sai Krishna Revanth Vuruma, Vishal Pallagani, Bharath Muppasani, Biplav Srivastava
Increasingly powerful Large Language Model (LLM) based chatbots, like ChatGPT and Bard, are becoming available to users that have the potential to revolutionize the quality of decision-making achieved by the public.
no code implementations • 25 May 2023 • Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan, Francesca Rossi, Biplav Srivastava, Lior Horesh, Francesco Fabiano, Andrea Loreggia
Firstly, we want to understand the extent to which LLMs can be used for plan generation.
no code implementations • 7 Mar 2023 • Francesco Fabiano, Vishal Pallagani, Marianna Bergamaschi Ganapini, Lior Horesh, Andrea Loreggia, Keerthiram Murugesan, Francesca Rossi, Biplav Srivastava
The concept of Artificial Intelligence has gained a lot of attention over the last decade.
no code implementations • 16 Dec 2022 • Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan, Francesca Rossi, Lior Horesh, Biplav Srivastava, Francesco Fabiano, Andrea Loreggia
Large Language Models (LLMs) have been the subject of active research, significantly advancing the field of Natural Language Processing (NLP).
no code implementations • 16 Dec 2022 • Bharath Muppasani, Vishal Pallagani, Kausik Lakkaraju, Shuge Lei, Biplav Srivastava, Brett Robertson, Andrea Hickerson, Vignesh Narayanan
Chatbots, or bots for short, are multi-modal collaborative assistants that can help people complete useful tasks.
no code implementations • 31 Mar 2022 • Vishal Pallagani, Priyadharsini Ramamurthy, Vedant Khandelwal, Revathy Venkataramanan, Kausik Lakkaraju, Sathyanarayanan N. Aakur, Biplav Srivastava
This demands a need for better representation of the recipes, overcoming the ambiguity and sparseness that exists in the current textual documents.
no code implementations • COLING 2020 • Shweta Yadav, Vishal Pallagani, Amit Sheth
One of the cardinal tasks in achieving robust medical question answering systems is textual entailment.
no code implementations • 9 May 2020 • Venkanna Udutalapally, Saraju P. Mohanty, Vishal Pallagani, Vedant Khandelwal
The deployment of the proposed system is demonstrated in a real-time environment using a microcontroller, solar sensor nodes with a camera module, and an mobile application for the farmers visualization of the farms.