44 citations · 114 across the 29 of their papers we have counts for
30 papers
Doing Less with More: A First-Principles Exploration of the Suitability of Agentic Computing over Alternative Architectural Choices
Ritvik Garimella, Biplav Srivastava, Amit Sheth
There is growing interest in automating business activities with Agentic Artificial Intelligence (AI) due to latter's seeming ease of use. Never has it been easier, or costlier, to…
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…
A Neurosymbolic Fast and Slow Architecture for Graph Coloring
Vedant Khandelwal, Vishal Pallagani, Biplav Srivastava +1
Constraint Satisfaction Problems (CSPs) present significant challenges to artificial intelligence due to their intricate constraints and the necessity for precise solutions. Existi…
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…
PLANTS: A Novel Problem and Dataset for Summarization of Planning-Like (PL) Tasks
Vishal Pallagani, Biplav Srivastava, Nitin Gupta
Text summarization is a well-studied problem that deals with deriving insights from unstructured text consumed by humans, and it has found extensive business applications. However,…
The Case for Developing a Foundation Model for Planning-like Tasks from Scratch
Biplav Srivastava, Vishal Pallagani
Foundation Models (FMs) have revolutionized many areas of computing, including Automated Planning and Scheduling (APS). For example, a recent study found them useful for planning p…
Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's Cube
Kausik Lakkaraju, Vedant Khandelwal, Biplav Srivastava +6
Artificial intelligence (AI) has the potential to transform education with its power of uncovering insights from massive data about student learning patterns. However, ethical and…
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…
The Effect of Human v/s Synthetic Test Data and Round-tripping on Assessment of Sentiment Analysis Systems for Bias
Kausik Lakkaraju, Aniket Gupta, Biplav Srivastava +2
Sentiment Analysis Systems (SASs) are data-driven Artificial Intelligence (AI) systems that output polarity and emotional intensity when given a piece of text as input. Like other…
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…
Value-based Fast and Slow AI Nudging
Marianna B. Ganapini, Francesco Fabiano, Lior Horesh +7
Nudging is a behavioral strategy aimed at influencing people's thoughts and actions. Nudging techniques can be found in many situations in our daily lives, and these nudging techni…
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…
Towards Explainable and Safe Conversational Agents for Mental Health: A Survey
Surjodeep Sarkar, Manas Gaur, L. Chen +3
Virtual Mental Health Assistants (VMHAs) are seeing continual advancements to support the overburdened global healthcare system that gets 60 million primary care visits, and 6 mill…
Fast and Slow Planning
Francesco Fabiano, Vishal Pallagani, Marianna Bergamaschi Ganapini +5
The concept of Artificial Intelligence has gained a lot of attention over the last decade. In particular, AI-based tools have been employed in several scenarios and are, by now, pe…
Advances in Automatically Rating the Trustworthiness of Text Processing Services
Biplav Srivastava, Kausik Lakkaraju, Mariana Bernagozzi +1
AI services are known to have unstable behavior when subjected to changes in data, models or users. Such behaviors, whether triggered by omission or commission, lead to trust issue…
Rating Sentiment Analysis Systems for Bias through a Causal Lens
Kausik Lakkaraju, Biplav Srivastava, Marco Valtorta
Sentiment Analysis Systems (SASs) are data-driven Artificial Intelligence (AI) systems that, given a piece of text, assign one or more numbers conveying the polarity and emotional…
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…
A Rich Recipe Representation as Plan to Support Expressive Multi Modal Queries on Recipe Content and Preparation Process
Vishal Pallagani, Priyadharsini Ramamurthy, Vedant Khandelwal +4
Food is not only a basic human necessity but also a key factor driving a society's health and economic well-being. As a result, the cooking domain is a popular use-case to demonstr…
Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments
Marianna B. Ganapini, Murray Campbell, Francesco Fabiano +8
Current AI systems lack several important human capabilities, such as adaptability, generalizability, self-control, consistency, common sense, and causal reasoning. We believe that…
ULTRA: A Data-driven Approach for Recommending Team Formation in Response to Proposal Calls
Biplav Srivastava, Tarmo Koppel, Sai Teja Paladi +3
We introduce an emerging AI-based approach and prototype system for assisting team formation when researchers respond to calls for proposals from funding agencies. This is an insta…