Tathagata Chakraborti

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Arizona State University ∙ ibm

Ph.D. student at Arizona State University

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

Existing approaches for the design of interpretable agent behavior consi...
11/22/2020 ∙ by Sarath Sreedharan, et al. ∙ 0 ∙ share

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Explainable Composition of Aggregated Assistants

A new design of an AI assistant that has become increasingly popular is ...
11/21/2020 ∙ by Sarath Sreedharan, et al. ∙ 0 ∙ share

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From Robotic Process Automation to Intelligent Process Automation: Emerging Trends

In this survey, we study how recent advances in machine intelligence are...
07/27/2020 ∙ by Tathagata Chakraborti, et al. ∙ 30 ∙ share

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Designing Environments Conducive to Interpretable Robot Behavior

Designing robots capable of generating interpretable behavior is a prere...
07/02/2020 ∙ by Anagha Kulkarni, et al. ∙ 21 ∙ share

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The Emerging Landscape of Explainable AI Planning and Decision Making

In this paper, we provide a comprehensive outline of the different threa...
02/26/2020 ∙ by Tathagata Chakraborti, et al. ∙ 47 ∙ share

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CLAI: A Platform for AI Skills on the Command Line

This paper reports on the open source project CLAI (Command Line AI), ai...
01/31/2020 ∙ by Mayank Agarwal, et al. ∙ 31 ∙ share

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D3BA: A Tool for Optimizing Business Processes Using Non-Deterministic Planning

This paper builds upon recent work in the declarative design of dialogue...
01/08/2020 ∙ by Tathagata Chakraborti, et al. ∙ 20 ∙ share

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A Unified Conversational Assistant Framework for Business Process Automation

Business process automation is a booming multi-billion-dollar industry t...
01/07/2020 ∙ by Yara Rizk, et al. ∙ 23 ∙ share

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Planning for Goal-Oriented Dialogue Systems

Generating complex multi-turn goal-oriented dialogue agents is a difficu...
10/17/2019 ∙ by Christian Muise, et al. ∙ 54 ∙ share

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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...
03/18/2019 ∙ by Sarath Sreedharan, et al. ∙ 18 ∙ share

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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...
11/23/2018 ∙ by Tathagata Chakraborti, et al. ∙ 0 ∙ share

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Plan Explanations as Model Reconciliation -- An Empirical Study

Recent work in explanation generation for decision making agents has loo...
02/03/2018 ∙ by Tathagata Chakraborti, et al. ∙ 0 ∙ share

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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...
01/30/2018 ∙ by Tathagata Chakraborti, et al. ∙ 0 ∙ share

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Visualizations for an Explainable Planning Agent

In this paper, we report on the visualization capabilities of an Explain...
09/13/2017 ∙ by Tathagata Chakraborti, et al. ∙ 0 ∙ share

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Mr. Jones -- Towards a Proactive Smart Room Orchestrator

In this paper, we report work in progress on the development of Mr. Jone...
09/13/2017 ∙ by Tathagata Chakraborti, et al. ∙ 0 ∙ share

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Balancing Explicability and Explanation in Human-Aware Planning

Human aware planning requires an agent to be aware of the intentions, ca...
08/01/2017 ∙ by Sarath Sreedharan, et al. ∙ 0 ∙ share

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AI Challenges in Human-Robot Cognitive Teaming

Among the many anticipated roles for robots in the future is that of bei...
07/15/2017 ∙ by Tathagata Chakraborti, et al. ∙ 0 ∙ share

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Plan Explanations as Model Reconciliation: Moving Beyond Explanation as Soliloquy

When AI systems interact with humans in the loop, they are often called ...
01/28/2017 ∙ by Tathagata Chakraborti, et al. ∙ 0 ∙ share

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Explicablility as Minimizing Distance from Expected Behavior

In order to have effective human AI collaboration, it is not simply enou...
11/16/2016 ∙ by Anagha Kulkarni, et al. ∙ 0 ∙ share

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UbuntuWorld 1.0 LTS - A Platform for Automated Problem Solving & Troubleshooting in the Ubuntu OS

In this paper, we present UbuntuWorld 1.0 LTS - a platform for developin...
09/27/2016 ∙ by Tathagata Chakraborti, et al. ∙ 0 ∙ share

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Proactive Decision Support using Automated Planning

Proactive decision support (PDS) helps in improving the decision making ...
06/24/2016 ∙ by Satya Gautam Vadlamudi, et al. ∙ 0 ∙ share

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Plan Explicability and Predictability for Robot Task Planning

Intelligent robots and machines are becoming pervasive in human populate...
11/25/2015 ∙ by Yu Zhang, et al. ∙ 0 ∙ share

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Tathagata Chakraborti

Featured Co-authors

Yu Zhang

Subbarao Kambhampati

Kartik Talamadupula

Murray Campbell

David Smith

Biplav Srivastava

Sarath Sreedharan

Vinod Muthusamy

Hankz Hankui Zhuo

Yasaman Khazaeni

Matthias Scheutz

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

Explainable Composition of Aggregated Assistants

From Robotic Process Automation to Intelligent Process Automation: Emerging Trends

Designing Environments Conducive to Interpretable Robot Behavior

The Emerging Landscape of Explainable AI Planning and Decision Making

CLAI: A Platform for AI Skills on the Command Line

D3BA: A Tool for Optimizing Business Processes Using Non-Deterministic Planning

A Unified Conversational Assistant Framework for Business Process Automation

Planning for Goal-Oriented Dialogue Systems

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

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

Plan Explanations as Model Reconciliation -- An Empirical Study

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

Visualizations for an Explainable Planning Agent

Mr. Jones -- Towards a Proactive Smart Room Orchestrator

Balancing Explicability and Explanation in Human-Aware Planning

AI Challenges in Human-Robot Cognitive Teaming

Plan Explanations as Model Reconciliation: Moving Beyond Explanation as Soliloquy

Explicablility as Minimizing Distance from Expected Behavior

UbuntuWorld 1.0 LTS - A Platform for Automated Problem Solving & Troubleshooting in the Ubuntu OS

Proactive Decision Support using Automated Planning

Plan Explicability and Predictability for Robot Task Planning