Subbarao Kambhampati

research

∙ 05/26/2023

Learning and Leveraging Verifiers to Improve Planning Capabilities of Pre-trained Language Models

There have been wide spread claims in the literature about the emergent ...

0 Daman Arora, et al. ∙

research

∙ 05/25/2023

On the Planning Abilities of Large Language Models – A Critical Investigation

Intrigued by the claims of emergent reasoning capabilities in LLMs train...

0 Karthik Valmeekam, et al. ∙

research

∙ 02/28/2023

Methods and Mechanisms for Interactive Novelty Handling in Adversarial Environments

Learning to detect, characterize and accommodate novelties is a challeng...

0 Tung Thai, et al. ∙

research

∙ 02/17/2023

Exploiting Unlabeled Data for Feedback Efficient Human Preference based Reinforcement Learning

Preference Based Reinforcement Learning has shown much promise for utili...

0 Mudit Verma, et al. ∙

research

∙ 02/17/2023

A State Augmentation based approach to Reinforcement Learning from Human Preferences

Reinforcement Learning has suffered from poor reward specification, and ...

0 Mudit Verma, et al. ∙

research

∙ 02/17/2023

Data Driven Reward Initialization for Preference based Reinforcement Learning

Preference-based Reinforcement Learning (PbRL) methods utilize binary fe...

0 Mudit Verma, et al. ∙

research

∙ 01/29/2023

A Mental Model Based Theory of Trust

Handling trust is one of the core requirements for facilitating effectiv...

0 Zahra Zahedi, et al. ∙

research

∙ 10/26/2022

Using Deception in Markov Game to Understand Adversarial Behaviors through a Capture-The-Flag Environment

Identifying the actual adversarial threat against a system vulnerability...

0 Siddhant Bhambri, et al. ∙

research

∙ 10/07/2022

Advice Conformance Verification by Reinforcement Learning agents for Human-in-the-Loop

Human-in-the-loop (HiL) reinforcement learning is gaining traction in do...

0 Mudit Verma, et al. ∙

research

∙ 02/18/2022

A Mental-Model Centric Landscape of Human-AI Symbiosis

There has been significant recent interest in developing AI agents capab...

0 Zahra Zahedi, et al. ∙

research

∙ 10/19/2021

Gradient-Based Mixed Planning with Discrete and Continuous Actions

Dealing with planning problems with both discrete logical relations and ...

0 Kebing Jin, et al. ∙

research

∙ 09/15/2021

Synthesizing Policies That Account For Human Execution Errors Caused By State-Aliasing In Markov Decision Processes

When humans are given a policy to execute, there can be policy execution...

0 Sriram Gopalakrishnan, et al. ∙

research

∙ 07/09/2021

Integrating Planning, Execution and Monitoring in the presence of Open World Novelties: Case Study of an Open World Monopoly Solver

The game of monopoly is an adversarial multi-agent domain where there is...

0 Sriram Gopalakrishnan, et al. ∙

research

∙ 06/23/2021

Not all users are the same: Providing personalized explanations for sequential decision making problems

There is a growing interest in designing autonomous agents that can work...

0 Utkarsh Soni, et al. ∙

research

∙ 05/03/2021

Trust-Aware Planning: Modeling Trust Evolution in Longitudinal Human-Robot Interaction

Trust between team members is an essential requirement for any successfu...

0 Zahra Zahedi, et al. ∙

research

∙ 05/02/2021

Planning for Proactive Assistance in Environments with Partial Observability

This paper addresses the problem of synthesizing the behavior of an AI a...

0 Anagha Kulkarni, et al. ∙

research

∙ 04/21/2021

A Unifying Bayesian Formulation of Measures of Interpretability in Human-AI

Existing approaches for generating human-aware agent behaviors have cons...

0 Sarath Sreedharan, et al. ∙

research

∙ 03/18/2021

Human-AI Symbiosis: A Survey of Current Approaches

In this paper, we aim at providing a comprehensive outline of the differ...

0 Zahra Zahedi, et al. ∙

research

∙ 11/24/2020

Model Elicitation through Direct Questioning

The future will be replete with scenarios where humans are robots will b...

1 Sachin Grover, et al. ∙

research

∙ 11/22/2020

A Bayesian Account of Measures of Interpretability in Human-AI Interaction

Existing approaches for the design of interpretable agent behavior consi...

0 Sarath Sreedharan, et al. ∙

research

∙ 11/19/2020

RADAR-X: An Interactive Interface Pairing Contrastive Explanations with Revised Plan Suggestions

Empowering decision support systems with automated planning has received...

0 Karthik Valmeekam, et al. ∙

research

∙ 10/28/2020

Model Minimization For Online Predictability

For humans in a teaming scenario, context switching between reasoning ab...

0 Sriram Gopalakrishnan, et al. ∙

research

∙ 10/08/2020

Moving Target Defense for Robust Monitoring of Electric Grid Transformers in Adversarial Environments

Electric power grid components, such as high voltage transformers (HVTs)...

0 Sailik Sengupta, et al. ∙

research

∙ 07/20/2020

Multi-agent Reinforcement Learning in Bayesian Stackelberg Markov Games for Adaptive Moving Target Defense

The field of cybersecurity has mostly been a cat-and-mouse game with the...

22 Sailik Sengupta, et al. ∙

research

∙ 07/02/2020

Designing Environments Conducive to Interpretable Robot Behavior

Designing robots capable of generating interpretable behavior is a prere...

21 Anagha Kulkarni, et al. ∙

research

∙ 02/26/2020

The Emerging Landscape of Explainable AI Planning and Decision Making

In this paper, we provide a comprehensive outline of the different threa...

47 Tathagata Chakraborti, et al. ∙

research

∙ 02/05/2020

`Why not give this work to them?' Explaining AI-Moderated Task-Allocation Outcomes using Negotiation Trees

The problem of multi-agent task allocation arises in a variety of scenar...

1 Zahra Zahedi, et al. ∙

research

∙ 02/04/2020

Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Black Box Simulators

As more and more complex AI systems are introduced into our day-to-day l...

4 Sarath Sreedharan, et al. ∙

research

∙ 10/15/2019

Challenges of Human-Aware AI Systems

From its inception, AI has had a rather ambivalent relationship to human...

45 Subbarao Kambhampati, et al. ∙

research

∙ 08/26/2019

Learning Action Models from Disordered and Noisy Plan Traces

There is increasing awareness in the planning community that the burden ...

1 Hankz Hankui Zhuo, et al. ∙

research

∙ 05/25/2019

Balancing Goal Obfuscation and Goal Legibility in Settings with Cooperative and Adversarial Observers

In order to be useful in the real world, AI agents need to plan and act ...

2 Anagha Kulkarni, et al. ∙

research

∙ 05/02/2019

A Survey of Moving Target Defenses for Network Security

Network defense techniques based on traditional tools, techniques, and p...

0 Sailik Sengupta, et al. ∙

research

∙ 03/19/2019

Why Couldn't You do that? Explaining Unsolvability of Classical Planning Problems in the Presence of Plan Advice

Explainable planning is widely accepted as a prerequisite for autonomous...

2 Sarath Sreedharan, et al. ∙

research

∙ 03/18/2019

Planning with Explanatory Actions: A Joint Approach to Plan Explicability and Explanations in Human-Aware Planning

In this work, we formulate the process of generating explanations as mod...

18 Sarath Sreedharan, et al. ∙

research

∙ 03/17/2019

Model-Free Model Reconciliation

Designing agents capable of explaining complex sequential decisions rema...

32 Sarath Sreedharan, et al. ∙

research

∙ 03/01/2019

To Monitor or to Trust: Observing Robot's Behavior based on a Game-Theoretic Model of Trust

In scenarios where a robot generates and executes a plan, there may be i...

2 Sailik Sengupta, et al. ∙

research

∙ 03/01/2019

To Monitor Or Not: Observing Robot's Behavior based on a Game-Theoretic Model of Trust

In scenarios where a robot generates and executes a plan, there may be i...

0 Sailik Sengupta, et al. ∙

research

∙ 12/23/2018

Markov Game Modeling of Moving Target Defense for Strategic Detection of Threats in Cloud Networks

The processing and storage of critical data in large-scale cloud network...

26 Ankur Chowdhary, et al. ∙

research

∙ 12/02/2018

Plan-Recognition-Driven Attention Modeling for Visual Recognition

Human visual recognition of activities or external agents involves an in...

0 Yantian Zha, et al. ∙

research

∙ 11/24/2018

TGE-viz : Transition Graph Embedding for Visualization of Plan Traces and Domains

Existing work for plan trace visualization in automated planning uses pi...

0 Sriram Gopalakrishnan, et al. ∙

research

∙ 11/23/2018

Explicability? Legibility? Predictability? Transparency? Privacy? Security? The Emerging Landscape of Interpretable Agent Behavior

There has been significant interest of late in generating behavior of ag...

0 Tathagata Chakraborti, et al. ∙

research

∙ 11/09/2018

Imagining an Engineer: On GAN-Based Data Augmentation Perpetuating Biases

The use of synthetic data generated by Generative Adversarial Networks (...

17 Niharika Jain, et al. ∙

research

∙ 03/07/2018

Extracting Action Sequences from Texts Based on Deep Reinforcement Learning

Extracting action sequences from texts in natural language is challengin...

0 Wenfeng Feng, et al. ∙

research

∙ 03/04/2018

Discovering Underlying Plans Based on Shallow Models

Plan recognition aims to discover target plans (i.e., sequences of actio...

0 Hankz Hankui Zhuo, et al. ∙

research

∙ 02/19/2018

Hierarchical Expertise-Level Modeling for User Specific Robot-Behavior Explanations

There is a growing interest within the AI research community to develop ...

0 Sarath Sreedharan, et al. ∙

research

∙ 02/16/2018

Implicit Robot-Human Communication in Adversarial and Collaborative Environments

Users of AI systems may rely upon them to produce plans for achieving de...

0 Anagha Kulkarni, et al. ∙

research

∙ 02/03/2018

Plan Explanations as Model Reconciliation -- An Empirical Study

Recent work in explanation generation for decision making agents has loo...

0 Tathagata Chakraborti, et al. ∙

research

∙ 01/30/2018

Algorithms for the Greater Good! On Mental Modeling and Acceptable Symbiosis in Human-AI Collaboration

Effective collaboration between humans and AI-based systems requires eff...

0 Tathagata Chakraborti, et al. ∙

research

∙ 12/05/2017

Recognizing Plans by Learning Embeddings from Observed Action Distributions

Recent advances in visual activity recognition have raised the possibili...

0 Yantian Zha, et al. ∙

research

∙ 11/20/2017

What's up with Privacy?: User Preferences and Privacy Concerns in Intelligent Personal Assistants

The recent breakthroughs in Artificial Intelligence (AI) have allowed in...

0 Lydia Manikonda, et al. ∙

Subbarao Kambhampati

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