44 citations · 72 across the 11 of their papers we have counts for
11 papers
Towards Information-Optimized Multi-Agent Path Finding: A Hybrid Framework with Reduced Inter-Agent Information Sharing
Bharath Muppasani, Ritirupa Dey, Biplav Srivastava +1
Multi-agent pathfinding (MAPF) remains a critical problem in robotics and autonomous systems, where agents must navigate shared spaces efficiently while avoiding conflicts. Traditi…
SafeChat: A Framework for Building Trustworthy Collaborative Assistants and a Case Study of its Usefulness
Biplav Srivastava, Kausik Lakkaraju, Nitin Gupta +3
Collaborative assistants, or chatbots, are data-driven decision support systems that enable natural interaction for task completion. While they can meet critical needs in modern so…
Towards Effective Planning Strategies for Dynamic Opinion Networks
Bharath Muppasani, Protik Nag, Vignesh Narayanan +2
In this study, we investigate the under-explored intervention planning aimed at disseminating accurate information within dynamic opinion networks by leveraging learning strategies…
On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS)
Vishal Pallagani, Kaushik Roy, Bharath Muppasani +7
Automated Planning and Scheduling is among the growing areas in Artificial Intelligence (AI) where mention of LLMs has gained popularity. Based on a comprehensive review of 126 pap…
On Solving the Rubik's Cube with Domain-Independent Planners Using Standard Representations
Bharath Muppasani, Vishal Pallagani, Biplav Srivastava +1
Rubik's Cube (RC) is a well-known and computationally challenging puzzle that has motivated AI researchers to explore efficient alternative representations and problem-solving meth…
Can LLMs be Good Financial Advisors?: An Initial Study in Personal Decision Making for Optimized Outcomes
Kausik Lakkaraju, Sai Krishna Revanth Vuruma, Vishal Pallagani +2
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 deci…
A Planning Ontology to Represent and Exploit Planning Knowledge for Performance Efficiency
Bharath Muppasani, Vishal Pallagani, Biplav Srivastava +3
Ontologies are known for their ability to organize rich metadata, support the identification of novel insights via semantic queries, and promote reuse. In this paper, we consider t…
Understanding the Capabilities of Large Language Models for Automated Planning
Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan +5
Automated planning is concerned with developing efficient algorithms to generate plans or sequences of actions to achieve a specific goal in a given environment. Emerging Large Lan…
On Safe and Usable Chatbots for Promoting Voter Participation
Bharath Muppasani, Vishal Pallagani, Kausik Lakkaraju +5
Chatbots, or bots for short, are multi-modal collaborative assistants that can help people complete useful tasks. Usually, when chatbots are referenced in connection with elections…
Plansformer: Generating Symbolic Plans using Transformers
Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan +5
Large Language Models (LLMs) have been the subject of active research, significantly advancing the field of Natural Language Processing (NLP). From BERT to BLOOM, LLMs have surpass…
A Dataset and Baseline Approach for Identifying Usage States from Non-Intrusive Power Sensing With MiDAS IoT-based Sensors
Bharath Muppasani, Cheyyur Jaya Anand, Chinmayi Appajigowda +2
The state identification problem seeks to identify power usage patterns of any system, like buildings or factories, of interest. In this challenge paper, we make power usage datase…